This PDF file contains the front matter associated with SPIE Proceedings Volume 11205 including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

Two types of tunable polarization-independent two-dimensional grating guided-mode resonance (GMR) filters are proposed and analyzed. The GMR filters are based on 2D crossed sinusoidal diffraction grating to archive polarizationindependent reflectance spectra and can be fabricated by using low-cost nanoimprinting process. The first GMR filter structure is consisted of three layers, including a planar waveguide, a low refractive index separation layer, and a nanoimprinting grating layer and the other has only two layers. The diffraction efficiencies are investigated by rigorous coupled-wave analysis (RCWA) method. For these two filters, by altering the incident and azimuth angle, the resonance wavelength of the proposed GMR filter is tunable and polarization-independent, and TE- and TM-polarized incident light can have the same diffraction efficiencies by adjusting the azimuth angle. For the first GMR structure with a grating period of 416 nm, the simulation results show that when the incident angle varying from 15° to 19° and the azimuth angle is set at 34°, the tunability in resonance wavelength is at a slope of 3.8 nm/degree. At the incident angle of 17° and azimuthal angle of 34°, the lowest difference of the diffraction efficiencies between two polarizations is approximately 0.23% at the resonance wavelength of 686.3 nm. The average diffraction efficiencies are 45.33% (TE polarization) and 44.94% (TM polarization). For the second GMR structure with a grating period of 555 nm, the simulation results show that when the incident angle varying from the same 15° to 19° and the azimuth angle is set at 38°, the tunability in resonance wavelength is at a slope of 6.5 nm/degree.

Dissimilar joining between metals has been always a desired need by many industries mainly on automotive. The urge to replace the conventional joining methods to a flexible technique such as fiber laser beam welding has created the demand for more feasibility studies on dissimilar metals. Despite of their thermal coefficient differences in them, the time reduction and higher productivity using fiber laser welding has led to studies on dissimilar nickel alloy, Inconel 600 and aluminum alloy; AA2024-0. Both these metals were laser welded at overlap configuration without any filler in between at a low power Yb-fiber laser. The feasibility studies proved optimum welding speed can influence the joining possibilities and the results can be investigated using optical microscopy (OM). The cross-section of the joints revealed that the fusion zone (FZ) and heat affected zones (HAZ) are wider when welding speed decreases with lower laser power. The energy from low power fiber laser is able to melt the parent metals forming a molten pool to allow liquid metal to flow smoothly between top and bottom layers. It can be concluded that further studies on laser welding with a low laser power between non-ferrous metals are possible.

Terahertz (THz) radiation, as a low-risk and high-efficient radiation has attracted especial attention and development of compact and efficient THz sources for various applications is of considerable interest. Wavelength conversion in the standard optical fibers was first observed and investigated based on the nonlinear phenomenon known as the scalar modulation instability (SMI). Compared with standard silica-based optical fibers, silicon waveguides have advantages such as higher refractive index and lower absorption loss over the THz region. The SMI can be analyzed based on the FWM process and in order to satisfy the phase-matching condition, the dispersion characteristics of the silicon waveguide must be well engineered. To this end, the pump wavelength must be adjusted very close to the zerodispersion wavelength (ZDW) of the waveguide. There are many methods which can be used to engineer the dispersion curve; one of them is changing geometrical parameters of the waveguide. In this paper, a silicon waveguide based on the photonic crystal idea is designed for the first time, and using the SMI phenomenon, tunable wavelength conversion for generation of THz radiation is simulated. By changing the geometrical parameters such as the air hole diameter of the photonic crystal, dispersion and nonlinear characteristics of the waveguide are controlled and hence the generated THz radiation is tuned. The results show when the pump wavelength is set at λ_p=5.60 μm in the normal dispersion regime and for the fixed lattice pitch of Λ= 4.80μm, as the air hole diameter is changing from d=4.60μm to d=0.86μm, the converted wavelength is tuned from λ=2.15μm to λ=326.17μm, respectively.

Digital holographic microscopy is a well-known powerful technique for quantitative phase measurement. However, the object phase is always embedded in aberrations. Here, a simple numerical compensation method based on rotation and transpose is reported. At first, we can obtain transpose phase by doing transpose transformation for original unwrapped phase. After subtracting transpose phase from original unwrapped phase, the subtraction phase is obtained and parts of aberrations also can be compensated. Subsequently, the rotation phase is obtained by doing rotation transformation with 180° for subtraction phase. Then, the residual phase aberrations are eliminated by subtracting rotation phase from subtraction phase. Not only off-axis tilt and parabolic phase aberration but also high order aberrations are removed without fitting operation or prior parameter of the specimen. The great performance makes our scheme available for single-shot quantitative phase imaging. The simulation results demonstrate the feasibility of our proposal.

In this paper, we study the diffraction properties of tunable cascaded VHGs by using the two-dimensional coupled wave theory and two-dimensional Runge-Kutta methods. The intensity distributions of the diffracted and transmitted beams are given, the total diffraction efficiency is calculated for multiple cascaded finite-sized VHGs. It is shown that the diffraction characteristics depend on the grating parameters such as the number of the cascaded VHGs and the sizes of each VHG, and the effects of the buffer gaps between two cascaded VHGs is also discussed. It demonstrates the possibility of shaping beam and improving the beam quality by controlling the grating parameters and the layers number of the VHGs. The analysis of this paper also will be valuable for novel applications of finite-sized VHGs.

A new phase analysis method using mean intensity values on electronic speckle pattern interferometry is proposed for measuring dynamic phenomena with variations of the mean intensity and the modulation amplitude values. In this method, phase differences are calculated by least-squares in kernels using interfered intensity values and mean intensity values of laser speckle pattern images on series deformation states. The interfered images and the mean intensity images are captured simultaneously for each state. For the phase difference calculation, initial phase values are required only for first step. The initial phases are obtained by another phase analysis method. The effectiveness of the proposed method is evaluated using simulation images. As a result, it is verified that the high accuracy phase analysis is possible under the situation with variations of the mean intensity and the modulation amplitude values. Additionally, an interferometer that two images, the interfered speckle image and the mean intensity image, are captured on a single image on a single camera is constructed for measuring displacement distribution. Experiments are then performed for validating availability of the proposed method.

With the development of technology, the demands for high-speed and high-precision processing for fabricating precision parts such as semiconductors and liquid crystals have been increasing. However, there is a problem that vibrations occur in ultra-precision machines. However, in order to improve machining accuracy, it is necessary to suppress the vibration of the machine tool. In a vibration control system, vibration is reduced by speed feedback. In the conventional method, speed control is performed by integrating acceleration. Therefore, there is a problem that the error is accumulated and the accuracy of measurement speed is reduced. Currently, linear velocity can’t be measured directly without reference point, while angular velocity can be measured directly without reference. The angular velocity can be measured directly using the Sagnac effect, which is the basis of the optical gyro. Then, in this research, in order to realize the linear velocity measurement method which does not cause an error theoretically, we verified about the direct measurement principle of linear velocity using Sagnac effect.

Camera/projector defocusing is a method of generating sinusoidal images for binary images in fringe projection profilometry. While the most appropriate degree of defocus is often difficult to determine. Therefore, in this paper, it is proposed a defocusing degree evaluation algorithm. This algorithm is to calculate the image gray value error E of the fitted sinusoidal image and the actual image based on image difference and Levenberg-Marquardt (LM) iteration method. Firstly, differential operation is performed on the image captured by the camera. And then, the LM iteration method is executed on the difference image. The phase fluctuation error E_M is quantitatively described as E ∙ S α by image gray range S, where α is constant which can be determined experimentally. For a system with no defocusing, the measured phase fluctuation error of ± 0.05 radian, this can be reduced to ± 0.01 radian under the optimal defocus degree obtained by this method. The algorithm can handle one image within 20 ms, which meets the requirements of real-time calculation.

Parallel computing of layer-based method for generating hologram of 3D objects is introduced. 3D MAX is used to model 3D object. The hologram of 3D model with depth information is calculated by Fresnel diffraction algorithm. The computational hologram generated by computer is reconstructed photoelectric to verify the correctness of the algorithm. This paper expounds the hardware architecture of GPU and CPU, briefly introduces the bottleneck and solution of CPU and GPU acceleration, and describes the optimization of thread and storage bandwidth in parallel processing. We use GPU hardware parallel computing and optimize the calculation process of 3D object hologram by using MKL and CUDA computing environment to improve the efficiency of computing. After analysis, the results show that the parallel computing speed of GPU hardware is 63 times faster than CPU alone. The parallel acceleration method can greatly shorten the computing time of generating hologram with layer-based method.

The lower mobility parallel mechanisms with the actuators mounted on the frame are suitable for picking and placing objects at high speed. The core design concept of the lower mobility pick-and-place parallel mechanisms, such as Delta mechanism, is that all kinematic limbs include parallelogram closed-loop sub-chain which can ensures the end effector to complete translation. For the occasions of carrying and grasping items in the plane where only two-dimensional translation is required, the use of the above mechanisms will cause a waste of utility functions and manufacturing costs. Under the premise of not changing the special geometry of parallelogram, a novel type of two-translation parallel mechanism based on a set of synchronous telescopic parallel links is proposed, which effectively reduce the size of the mechanism itself and increase the working range in the vertical direction. The mechanism can complete the grasping of objects scattered on the belt on the basis of visual guidance. Through the screw theory, the kinematic screw equation of the mechanism is established, and the analysis of mobility is implemented. In addition, kinematic studies are carried out on the two-translation parallel mechanism. Furthermore, the singularity is analyzed and workspace is calculated which are helpful in optimizing the mechanism.

The typical lens-free on-chip digital holographic microscopy (LFOCDHM) as a modern imaging technique produce compromised imaging resolution that far below the ideal coherent diffraction limit. At least five major factors may contribute to this limitation, namely, the sample-to-sensor distance, spatial and temporal coherence of the illumination, finite pixel size of the sensor, and finite extent of the image sub-field-of-view used for the reconstruction. In this paper, we derive five transfer function models that account for all these physical effects on the imaging resolution of LFOCDHM. The theoretical resolution limit of a given LFOCDHM system can also be predicted. Besides this, we provide a useful guide to the selection of different system parameters for the optimization of the imaging resolution when designing a new LFOCDHM system.

Electronic Speckle Interferometry (ESPI) is a common method for deformation measurements by introducing a phase shift technique. The traditional method needs to subtract the distribution of the phase before and after deformation to get the deformation information. During this process, the noise of the object wavefront will partially remain in the deformation signal. In order to solve this problem, this paper proposes a 5+5 phase-shifting algorithm to suppress the influence of the error from the calculation. In this algorithm, the deformed phase map is directly obtained by combining the interferograms before and after the deformation. Several experiments have been carried out to verify this method. Finally, the results show a better characteristic to quantify deformation than the traditional method. In addition, the algorithm also has better redundancy

Recently, with the increasing demand for high-accuracy three-dimensional (3D) imaging and localizing of the internal subcellular structures in cells, quantitative refractive index tomography technique has been developed and widely applied in various fields, such as molecular biology, biochemistry and cell biology. Thanks to the noninterference, large field of view and high resolution advantages of traditional Fourier ptychographic microscopy (FPM) technique, quantitative phase tomography (QPT) method based on multi-slice (MS) FPM has attracted considerable attention lately. However, since the reported MS model is simply established on the traditional two-dimensional FPM, it is difficult to characterize the 3D diffractive propagation properties under large oblique illumination angles accurately. In order to solve this problem, an improved MS model for 3D FPM is proposed in this paper. First, the phase difference image of each slice under the vertical illumination is regarded as the standard phase map. Then, based on the law of refraction, the true phase delay of each slice under large oblique illumination angle is established according to the 3D optical path difference variation. The numerical error between the true phase delay and the standard phase map is then compensated in the iterative reconstruction algorithm, and finally the reconstruction accuracy and quality of the 3D QPT could be improved.

Multi-frequency phase unwrapping algorithms (MFPUAs) are among the most robust and efficient phase unwrapping methods, and hence widely adopted in various optical measurement techniques, such as fringe projection profilometry, interferometry, and so on. However, if they are not well designed, or the measurement condition is poor, fringe order error (FOE) will be triggered during the phase unwrapping, which will result in phase unwrapping error. This paper is for coping with FOE without consuming additional fringe patterns for phase unwrapping. Firstly, a parameter called fringe order inaccuracy (FOI) which is applicable to the representative MFPUAs is defined. Secondly, FOI is employed to help quantify the possibility of the occurrence of FOE. Lastly, a fast FOE correction method is proposed with aid of FOI. Experiments validate that the proposed method contributes to suppressing FOE while keeps the efficiency of MFPUA.

In this research, we systematically investigated the image classification accuracy of Fourier Ptychography Microscopy (FPM). Multiple linear regression of image classification accuracy (dependent variable), PSNR and SSIM (independent variables) was performed. Notebly, results show that PSNR, SSIM, and image classification accuracy has a linear relationship. It is therefore feasible to predict the image classification accuracy only based on PSNR and SSIM. It is also found that image classification accuracy of the FPM is not universally significantly differed from the lower resolution image under the higher numerical aperture (NA) condition. The difference is yet much more pronounced under the lower NA condition.

The variation in state of polarization (SOP) in oceanic turbulence is studied using Electromagnetic multiGaussian Schell model(EM-MGSM)beams. The SOP and Degree of Polarization(DOP) variation at far zone is examined and noticed that effect on DOP and SOP is same for s₂ and s₃ Stokes parameters. The unpolarized light variation in turbulence is also studied. The radial distance propagation at two different values of z=250m and z=100km are compared and noticed about slower modification of DOP at higher value of z. We have shown that

We present a novel approach to compensate coherence effect via combining the transport of intensity equation (TIE) with look-up table phase compensation (LUT-PC) method. It is the better version of the Speckle-TIE method we demonstrated before on the basis of the quantitative phase imaging camera with a weak diffuser (QPICWD). With the phase gradient ratio theory and the look-up table method, the phase blurring caused by underestimation of phase gradient will be compensated correctly by reasonable rescaling. The LUT-PC SpeckleTIE method has the evident predominance of speediness since it only needs one slightly defocused speckle image in one time owing to that the reference speckle image can be captured beforehand. The deblurring achieved by this method improves the imaging resolution to the theoretical partial coherence limit with good robustness, reducing artifacts and improving the accuracy and contrast. The experimental results show the effectiveness of the technique.

Quantitative phase imaging (QPI), which provides unique imaging capabilities for optical thickness variation of living cells and tissues without the need for specific staining or exogenous contrast agents (e.g., dyes or fluorophores), has emerged as an invaluable optical tool for biomedical research. Differential phase contrast (DPC) is the most promising QPI approach to high resolution label-free cellular dynamic imaging because of its advantages of higher imaging efficiency, higher accuracy, and higher stability. Typically, illuminations in DPC systems are designed with 2-axis half-circle amplitude patterns, which however results in a non-isotropic phase transfer function (PTF). Furthermore, the frequency responses of the PTFs have not been fully optimized, leading to suboptimal phase contrast and signal-to-noise ratio (SNR) for phase reconstruction. In this paper, we derive the optimal illumination scheme to maximize the PTF response for both low and high frequencies (from 0 to 2NA_obj ), and meanwhile achieve perfectly isotropic PTF with only 2-axis intensity measurements. We present the theoretical analysis, simulations, and experimental results demonstrating that our optimal illumination scheme is a simple, efficient, and stable approach for label-free quantitative cell imaging with subcellular resolution.

Correlation filter based tracking methods are the core component of most trackers which achieve the excellent performance in term of the accuracy and robustness in visual tracking. However, there are still lots of challenging situations, such as occlusion or illumination, which confines and limits the performance of trackers. To cope with the above problems, in this paper, we suggest an effective tracking method via part-based strategy. Compared with the conventional tracking algorithms based on correlation filter, our tracker employs the novel strategy to validate and estimate the target’s final position, avoiding merely utilizing the maximum response in the response map as the target position which is often prone to drift away from the target. In addition, to effectively deal with occlusion, we divide the sample into multiple parts. When the sample is partly occluded, the visible part can still provide effective clues for tracking, ensuring the robustness of tracker. A large number of conveys are conducted on the public databases, and experimental results show that the proposed algorithm has obvious performance improvement in the case of dealing with target occlusion, and the real-time performance is also pretty good.

When imaging through an undulating clear water surface, a complex series of refractions and reflections occur throughout the imaging path, and light rays are bent by unknown amounts. So the captured images usually contain severe geometric distortions. In this paper, an iterative robust registration algorithm is employed to remove the distortions in frames by registering each frame to a reference image. As the traditional image registration algorithm is impeded by the severely blur mean, we decide to reconstruct a high quality reference as the surrogate of the mean. We first select the image patches with higher quality from the distorted sequence to reconstruct a single image. In the patches selection process, the image quality of patches is evaluated from sharpness and geometric distortion. Then the blind deconvolution technique is employed to deblur the image, which will be used as a reference of the next registration process. Experiment shows that the proposed algorithm performs well in restoring the distorted underwater images and has less computational time than the state-of-the-art method.

Flexible-electronics is gaining increasing popularity in microelectronics such as flexible display, smart skin, epidermal electronics and soft robotics due to cost-effective fabrication and possibility of obtaining multifunctional electronics over large areas. Distinct from conventional microelectronics, flexible curved substrate such as polyimide has been adopted in the flexible-electronics manufacturing process. Hence, how to measure the curved surfaces of the substrates in a precise and fast way has become a key issue. Traditionally, the curved surfaces are usually measured in a coordinate measuring machine (CMM). However, the polyimide substrates (<1mm) are so thin that they are vulnerable to be scratched and deformed. To solve the problem, this paper presents a 3D measuring system based on the laser displacement sensor, high precision motion platform and programmable multi-axis controller (PMAC). Meanwhile, to process the measured data and inspect the machining quality of the substrate by using the 3D matching methods, a software called iPoint3D was developed.

During the radiation therapy of the laryngeal tumor, the laryngeal motion occurred from swallowing can cause the tumor to move away from the radiation area and lead to a decline in treatment efficiency. Therefore, to detect the time of swallowing of a laryngeal cancer patient is essential for later remedial measures. However, since metal occlusion cannot be contained in front of the irradiation rays, many conventional detection methods cannot be used. This paper presents a Fiber Bragg Grating (FBG) based method for swallowing detection. The FBG sensor is attached to the thyroid cartilage of the human throat. The movement of the thyroid cartilage during the bending causes the FBG sensor to bend, causing the wavelength of the reflected light of the sensor to change. The change of the wavelength of the reflected light reflects the movement of the thyroid cartilage. In the experiment of healthy adults, both the camera and the FBG sensor were used to detect the movement of the throat during swallowing. The results of the camera detection were compared with the results of the sensor detection. The result illustrates that the FBG sensor can correctly count swallows and efficiently detect the swallowing movement time.

Fringe pattern denoising is an important process for fringe pattern analysis. In this paper, fringe pattern denoising using the convolutional neural network (CNN) is introduced. We use Gaussian functions to generate the various phase distributions, and then the required training samples are simulated according to theoretical formulas. The noisy fringe pattern can directly obtain the clean fringe pattern using the trained model. The denoising performance has been verified, which can recover high-quality fringe pattern.

Phase unwrapping is a general problem in many measurement fields, and plenty mature methods have been put up with. Among them, Laplacian operator combined Fast Fourier-based phase unwrapping method is widely used because of its high speed and relative robustness. However, in some applications such as structured-light 3D reconstruction, there always appear shadows of object in the object-edge regions. These shadows and discontinuity regions might cause big errors in unwrapping results, which will be even more serious for the Fast Fourier-based method. Therefore, in this paper, we analyzed the problem theoretically and present a modified algorithm based on the reference-phase mask. With a designed phase mask, this practical algorithm can remove errors effectively and reach a more precise result. The phase mask will be produced automatically based on the edge detection of the problematic regions combined with an empirical mode decomposition algorithm. The whole procedure will be complemented without manual intervention. Comparison experiments show that our method has great improvement than the original methods in the aspects of accuracy speed, and robustness. This enables the Laplacian based unwrapping algorithm to have compatibility with more optical, physical, medical and engineering occasions.

Palm veins images are taken by a near infrared camera and a common digital camera. It is possible to generate clear vein images using near-infrared rays, but this is not easy using a color image. A near infrared palm vein image for training data and a color image were arranged in a dataset pair; the datasets were learned using a deep learning method called pix2pix. Clear palm vein images close to the near infrared image were generated using our proposed method. Our experimental results showed that we can take a palm vein image using only a general digital camera without a near infrared camera. Realization of palm veins authentication on an inexpensive smartphone is expected.

Visual object tracking has become increasingly popular in the community due to its application and research significance. However, occlusion is one of the major factors that seriously impact the tracking performance in visual tracking. To address this issue, in this paper, we propose a novel nonlocal correlation filter based tracking method. Our proposed tracker effectively exploits the explicit coupled mechanism which depends on the global filter and several local part filters, and efficiently employs the spatial geometric constraints among the global object and local patches of object for preserving the structure of object. Compared with other existing correlation filter based trackers, our proposed tracking method has three advantages: (1) To ensure complete representation to the target candidate, we learn the correlation filers from not only the global sample but also local sample parts. The global based filter guarantees the overall accuracy of the tracked object, while the local based filters reserve the details of tracking object to cope with the challenging cases like occlusion or deformation. In addition, an effective and adaptive selection mechanism is proposed to select the most distinctive and discriminative parts for tracking, which avoids unnecessary computing burden caused by tracking all parts and simultaneously improves the robustness of the tracker. (2) Through adaptively weighting the global sample and each local part of samples, the integration mechanism puts more emphasis on visible parts and eliminates the impacts by occluded parts for further improving the tracking robustness. (3) Different from other trackers by searching for the predefined scale pyramid, we propose a simple yet effective scale estimation strategy which can accurately calculate the current scale of the tracking target. For verifying our method, we conduct extensive qualitative and quantitative experiments on challenging benchmark image sequences. Experiment results demonstrate that our proposed method performs favorably against several state-of-the-art trackers.

Existing motion-capture technologies are implemented through expensive and specialized equipment, which typically requires the wearable devices or the mark of human body joint. This leads to a distinct limitation on the accessibility and popularity for mass market consumer. To address these problems, we present a pipeline for 3D human motion capture from binocular stereo vision, which is based on MobilePose, a supervised learning method for 2D skeletal joint detection in real time. Due to the short time of 2D joint detection and 3D reconstruction, our approach can fulfill 3D human motion capture in real time. Besides, we use the captured 3D motion information to implement a simple application on human body animation. Compared with Microsoft's Kinect method using depth camera, our method is implemented with the available cameras, which is low cost and widely used.

A depth map and an RGB image taken by a light field camera for training data are arranged in a dataset pair; the datasets are learnt through a deep learning method called pix2pix, which is a type of conditional generative adversarial network. We can generate depth maps using only a monocular mobile camera without the light field camera based on our proposed method. Low accuracy on depth is a technical issue for the light field camera; however, the proposed method improves the depth accuracy due to the generalization ability of neural networks.

Up to date, fiber optics laser systems are the most efficient way to carry information and very important in the field of telecommunication in Thailand. Typical optical fiber systems composed of laser sources, optical fibers as the transmission mediums, and detectors as receivers, where the most basic measurement necessary is optical power. To maintain quality and standard of information transmission, optical power measurement calibration is very important. The objective of this research was to design and development of InGaAs detectors, to use as an optical power transfer standard in the wavelengths where the optical fiber communication systems are operated. The design and development of the transfer standard under scientific collaboration between the national institute of metrology Thailand (NIMT) and Germany (PTB) will be presented.

We demonstrate a stable passive Q-switched fiber laser operating at 1560 nm. To realize pulsing generation, a piece of rose gold as a saturable absorber. The self-started Q-switching operation presence from 35 mW and stable until 142 mW pump power. By increasing the pump power to maximum level, generated pulse train has a maximum repetition rate of 89.89 kHz and short pulse width of 2.64 μs with a pulse energy of 103.08 nJ. The maximum output power is 8.56 mW. The obtained pulse is stable with a signal-to-noise ratio of 69 dB at 35 mW pump level.

In this paper, a comparison study on the all fiber optic non-contact vibration sensors which are designed based on the principle of reflected light intensity modulation is reported. Various structural designs were proposed to enable advancement in the sensing of the vibration. For every configuration, achieved an improvement by eliminating the dark region, exhibits single slope which enables easy alignment and the rational output method used to eliminate the effect of light source on sensing. The comparison between dual plastic optical fiber, fiber optic fused 1x2 coupler and fiber optic fused 2x2 coupler vibration sensors have been discussed in detail with respect to the vibration measurement. The results reveal that, among all the reported vibration sensors 2x2 fiber optic coupler sensor exhibits better response in all the aspects. It has high resolution of 0.03 µm and frequency range up to 3.5 kHz.

In order to improve the working performance of the optical fiber spectrum analyzer, a spectrum analyzer with an ultrasmall gradient-index (GRIN) fiber probe was studied. The theoretical model of this spectrum analyzer was established and a near-infrared spectrum analyzer with an ultra-small GRIN fiber probe was constructed. The performance of the analyzer was demonstrated using a narrow bandpass filter. The experimental results show that the spectrum analyzer with the GRIN fiber probe can obtain higher output power than that with the single-mode fiber probe at the same distance. In addition, the spectrum analyzer with the GRIN fiber probe still has good performance within the range twice the working distance of the GRIN fiber probe, which is near 1 mm. However, the system with the single-mode probe can only work within the range of 0.4 mm. The results demonstrate that the spectrum analyzer with the GRIN fiber probe has better working performance.

This study focuses a new ratiometric optical fiber carbon dioxide (CO₂) sensor based on CdSe/ZnS QDs and pH sensitive dye Polym-H7, those were immobilized within the Ethyl cellulose (EC). These CO₂ sensing materials were coated on the surface of the optical fiber end and a 375 nm LED light was employed as an excitation source, it is shown that the emission wavelength of fluorescence dyes have no spectral overlap, so the fluorescence intensity ratio of two dyes can be used to design a ratiometric optical fiber CO₂ sensor. The experimental result reveals the sensitivity of ratiometric optical fiber carbon dioxide sensor as R₀/R=1.84 and exhibits a uniquely linear response for CO₂ concentrations in the range of 0-100%. The suggested new ratiometric sensing approach suppresses the effects of imitation fluctuations in the intensity of excitation source.

A novel short-cavity-based narrow linewidth random fiber laser (RFL) is proposed. The random distributed feedback mechanism of RFL is assumed by a set of arbitrarily distributed weak reflection fiber Bragg grating arrays (FBGs). A π-phase-shifted FBG with a narrow transmission window is used in the RFL to further limit the number of random subcavity modes and suppress the output linewidth. High gain erbium-doped fibers and half-open cavity designs are used to maintain low lasing thresholds. A stable single-mode lasing operation with 3-dB linewidth of 211 Hz and 58 dB sidemode-suppression-ratio is established.

This paper proposes a wavelength-division multiplexing fiber laser acoustic emission sensing technique based on 3×3 coupler type interrogation method and a FPGA parallel processing algorithm. Narrow-linewidth (about 3 kHz) singlefrequency distributed feedback fiber lasers are used for acoustic emission probes. A NI FlexRIO device is used to acquire the original signals from the photodetectors. A symmetric demodulation algorithm is executed in the FPGA using parallel data processing structure. The acoustic emission sensing system with four parallel channels and 2 MHz sampling rate achieves a wavelength resolution of 2 × 10^-7 pm/√Hz @ 100 kHz.

In this manuscript, the development of SMART sensing technology for applying in the industrial sector has been described. Specifically, the ten S-curve industries of Thailand, according to the 20 years national strategy (from 2018 to 2037), have been emphasized. However, the integration between the SMART sensing technology and the internet of things (IoT) has been considered as an important key for the development of modern sensing technology. The optical fiber sensor technology (OFS) is, consequently, one of the most widely utilized sensors nowadays, due to its superior aspects as compared to other conventional sensors. Moreover, this could be seen from the researches in precision measurements, for examples, the fiber optic sensor for leak detection of methane pipeline, development of continuous biogas measurement system based on OFS, and also the non-invasive fiber optic blood pressure monitoring device, etc. In addition, the artificial intelligence (AI) could be employed as a tool which enhances the performance of the OFS system, as seen with the examples of the artificial neural network (ANN) development in source localization through the fiber optic sensing array, incorporation of the fiber optic sensor and IoT to remotely monitor the structural safety of underground mine, machine learning for assisting the OFS in the prediction of gas generation, and so on. This, thus, improves the OFS into the more intelligent sensing devices. Furthermore, the distinctive points of the presented technologies have been reviewed, with capabilities for the modern applications, which could lead to the future national emergence into “Thailand industry 4.0”.

An automatic parts dimension inspection method based on scanned point cloud is proposed in this paper. Firstly, the point cloud and the CAD model are registered in the CAD model coordinate system by using Fast Global Registration algorithm. Then, by developing the dedicated inspection program based on the 3D modeling software, the dimensions of the CAD model and the features associated with these dimensions are retrieved, which includes edges, planes, cylinders, spheres, etc., and the dimensions also include the information such as the dimension type, the dimension symbol, the references of the dimension. And then, under the guidance of the dimension information extracted from the CAD model, the corresponding features in the point cloud can be extracted by using Random Sample Consensus algorithm. Finally, the dimensions associated with the extracted features can be calculated by fitting the point cloud features into geometric elements and then calculating the corresponding distance. The whole inspection procedure can be accomplished without human interaction. The feasibility and the accuracy of the proposed method is verified by carrying out the experiment of measuring the industrial parts.

Infrared Thermography is a non-contact technique for non-destructive evaluations that has been widely used for inspection of structural materials. The prediction of defect depth is the most obvious advantage compared with other non-destructive techniques. Several thermal signal processing technologies and quantitative measurement methods have been reported in literature. However, most of those methods are only applicable to Pulse Infrared Thermography and Lock-In Thermography. In this paper, Phase Fourier Analysis (PFA) was used to determine the defect location and Logarithm Second Derivative Time (LSDT) was used to calculate the defect depth with Long Pulse Thermography (LPT). The experimental results were compared with numerical simulations of a Glass Fiber Reinforced Plastics (GFRP) panel with predesigned defects. It is found that the thermal signal processing can enhance the defect contrast and the specific characterize time in LSDT has a linear relationship with the square of depth.

In order to solve the problem of precise detection of small modulus gear and break through the limitations of traditional detection methods such as measuring force, measuring diameter, gear thickness, easily damaged probe, high cost and low efficiency, this paper studies the principle and implementation method of precise detection of small modulus gear based on polychromatic laser confocal ranging technology and four-axis linkage motion platform. An adaptive optimal measurement path planning method based on the fixed distance and constant light intensity servo control method is proposed, which reduces the influence of the measurement spot size and incident angle on the measurement accuracy. The three-dimensional topological measurement method of small modulus gear tooth surface in non-contact measurement process and the adaptive matching calculation and analysis model of three-dimensional measured profile and theoretical profile are studied. The unification of single tooth surface matching and multi-tooth surface matching effect is realized, and the influence of clamping error on measurement accuracy is reduced. Finally, the accurate detection of gears whose modulus is less than or equal to 0.1 mm is realized. The measuring platform can measure gear part above ISO1328-2013 class 3.

This paper focused for possibility to use RGB-LED module as a tunable light source for absorption spectroscope. Nowadays, commercial instrument uses Xenon lamp with Monochromator to select a specific wavelength for tested some properties on a sample. This part is a core of performance in an instrument and it increase cost of an instrument. In this paper, RGB-LED module will replace for a part of Xenon lamp and Monochromator to select a specific wavelength for measurement absorption or transmission properties. By used Arduino controller with pulse-width modulation method (PWM), a specific wavelength can control by mixed light that emitted from RGB-LED module. Resolution from this method can tuned an optical wavelength in range of visible light (400-700 nm) by 5 nm. Results from this work had difference from the commercial instrument less than 5%. Accuracy of this setup was proved with standard deviation (SD) and uncertainty about 0.0904 and 0.0286. This work can apply for light source to studies absorption or transmission properties of material in basics laboratory.

A near infrared (NIR) spectroscopy model was used to quantitatively detect buffalo milk adulteration with cow milk. Pasteurized buffalo milk samples were purchased from a dairy farm and from a local supermarket. Adulterated milk samples were prepared with ratio of cow milk to buffalo milk at 9 levels of 10:90, 20:80, 30:70, 40:60, 50:50, 60:40, 70:30, 80:20 and 90:10 wt%. Spectra of pure buffalo milk, pure cow milk and adulterated milk samples were recorded by a Fourier transform NIR spectrometer in the wavenumber range of 12500-4000 cm^-1 with resolution of 8 cm^-1 . A NIR spectroscopy quantitative model was developed with partial least square (PLS) regression. The NIR spectroscopy model showed ability to detect adulterated milk as follows: R_val² = 0.998, RMSEP = 2.121 wt%, Bias = -0.396 wt% and RPD = 18.1. NIR spectroscopy coupled with PLS algorithm was shown to be an alternative technique to detect buffalo milk adulteration with cow milk in the global dairy industry.

The scattering energy distribution described by the bidirectional reflection distribution function (BRDF) is the most basic radiation property for calculating other properties. In order to characterize the effect of the surface topography of the optical component on the scattering properties, based on the first-order perturbation theory combined with the Rayleigh scattering model, considering the specular reflection and scattering, an improved polarization bidirectional reflection distribution function(pBRDF) is proposed based on the BRDF. The influence of factors such as the surface roughness and the incident angle of irradiation on the scattering distribution and the polarization scattering distribution are discussed. A series of experimental scattering distribution curves are obtained by designing and building an experimental device based on the BRDF theory. The experimental results are in good agreement with the numerical simulation data, which demonstrates the high accuracy of the pBRDF model. Finally, the power spectral density(PSD) is inverted by scattering measurement data. The results compared with the experimental data of CCI2000, verify the correctness of the proposed model. The present research offers an objective guidance for conducting surface quality detection in the field of precision optical components processing and for ensuring the optical transmission quality of precision optical systems.

Corrosion in metal structures is one of the prevailing problems impacting automobile, cargo, and construction industries. The detection of corrosion at the right time and determination of the root cause are crucial in its prevention and control. In this context, we propose hyperspectral imaging as a potential imaging modality for monitoring corrosion. This technique is very relevant for high-speed, non-destructive inspection. The proposed hyperspectral imager can efficiently monitor corrosion with high sensitivity and it enables corrosion detection even at human inaccessible areas with the aid of a custom fabricated fiber optic probe. In contrast to traditional methods, the hyperspectral imaging technique can capture reflectance at several wavelengths from several spatial points of the sample and hence provides a means of rigorous analysis of the sample reflectance. Using a two dimensional to one dimensional fiber bundle reformatter, hyperspectral images of metal samples were recorded. Induced corrosion in the sample was monitored by the hyperspectral imager and the data recorded were processed to form the three-dimensional spectral datacube. Obtained results show that hyperspectral reflectance imaging is a powerful tool for corrosion monitoring, non-destructively.

Optical security has attracted much attention in recent years, and much research work has been done to establish various optical security systems. It has been further found that when optical authentication is introduced into optical encryption systems, system security can be enhanced. Hence, authentication-based optical security has been widely studied. However, much previous work needs to use relatively complicated optical setups or algorithms to establish authentication-based optical security systems. In this paper, a simple method is presented by using direct wave propagation to generate a compressed phase-only mask as ciphertext, and the input image is compressed before the encoding. Results and analyses demonstrate that the proposed method is feasible and effective for authentication-based optical security. It is expected that the method presented can provide a promising approach for effectively enriching authentication-based optical security area.

Due to the excessively dense steel coil layers on the end face of the rolled coil, it is difficult to extract the defect area of the end face of rolled steel by the image segmentation methods such as edge detection and threshold segmentation. Aiming at the dense texture features of the end face of rolled steel coil, a method of detecting the defects of the end face of steel coils was proposed. Based on the theoretical technology of machine vision, this paper proposed a double threshold method to extract potential defect area and eliminate the background area and the completely defect-free area. In the double threshold method, we utilize the Canny operator and the PPHT (Progressive Probabilistic Hough Transform) to adjust the direction of the image block on the end face of the steel coils, makes the texture direction on each image block consistent. Then, Gaussian steerable filter, followed by second Canny and PPHT, was applied to enhance image. After the double threshold method, projective integral of digital image was utilized to extract the feature of the potential defects area. Finally, the SVM (Support Vector Machine) is applied to determine the type of the defect. The results show that the method of detecting the defects of the end face of steel coils can accurately and quickly detect defects even on the end face image of the steel coils with dense layers.

Spatial particle distribution can be recorded by holography technology and can be constructed from multi-layer hologram. Due to the influence of holographic recording and reconstruction process, each tomography of multi-layer reconstruction from holography also contains noise in addition to containing spatial particle distribution information. How to denoise each tomography is a key problem. The existing methods either have a long operation time or the noise reduction effect is not obvious. In order to solve the above problems, we proposed a denoising method based on deep learning in this paper. A deep neural network is built to train and test with simulated spatial particle tomography on multi-layer holography reconstruction. According to the simulation results, the method proposed in this paper is effective in denoising the reconstruction results of spatial particles. The proposed method has the advantages of rapidity and high efficiency.

Obstacles detection is one of the most important parts for ADAS (Advanced Driver Assistance Systems). Camera provides excellent recognition but with limits to range information; nevertheless, the LiDAR allows for better range information but with limits to the object identification. This paper deals with the problem of efficiently and accurately detecting vehicles on-load by fusing color images and LiDAR point clouds. Firstly, a neural network is used to detect road and vehicles. This neural network has high accuracy and speed on detection for the encoder in it is shared by different tasks. In the second step, the point clouds are processed to remove some invalid points and positions that potential represent targets generate by clustering point clouds. Positions are projected to images plane to get the ROI (Region of Interest), then the ROI will be matched with detection results of image to check if any targets are missed. In the paper, we adopt the RANSAC (Random Sample Consensus) algorithm to remove ground points. A parameter adaptive DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm is proposed to cluster points, where parameters can change adaptively according to the characteristics of different density point clouds. Through neural network, we recognize the types of obstacles. Experiment is performed on KITTI dataset, using left color images and Velodyne64 point clouds to verify our method. The result shows satisfactory accuracy in detection work.

Imaging through scattering media is a long-standing problem which has been extensively studied to promote the development of imaging in complex environments. Extant techniques for image reconstruction in scattering media face with the disadvantages of limited ranges of applications, high sensitivity to environmental changes and huge computational load. The scattering media commonly used in practical applications are more complicated due to unknown perturbations. One of the most outstanding problems is the uncertainty of the object position which obstructs progressive development of image recovery techniques. Therefore, it is meaningful to explore a feasible method to bypass additional requirements of precision measuring instruments. Here, we present a method based on convolution neural network (CNN) for optical image reconstruction. The targets are placed in the scattering media which are composed of a certain volume of water and milk, and their diffraction patterns are recorded by using a camera. The learning model demonstrated in this paper is tolerant to uncertainty of object positions. It is foreseeable to be a promising substitute for imaging objects in harsh environments.

When image through water turbulence, captured images will appear severe geometrical distortion. Restoration of image with unknown geometrical distortion is a challenging problem. In this paper, we propose an iterative method to acquire a geometrically corrected high-quality image from an observed video sequence which contains serious geometrical distortion. Firstly, we use a blind deconvolution method to deblur the temporal mean image of the observed video sequence. Next, an image registration based on B-spline is employed to obtain a new video sequence with less geometrical distortion. After several iterative computations of deconvolution and registration, we carry out a robust principal component analysis to remove residual noise of latest video sequence. Finally, a single geometrically corrected image is acquired by a temporal mean operation on final video sequence. Experimental results demonstrate that our proposed method is capable to greatly remove geometrical distortion in video sequence.

Surface defect recognition is used to test product’s quality. The current way of recognition is traditional 2D imagebased method. But 2D image lacks 3D information which results in false inspection and missed inspection, which has become a bottleneck of current classification model. Because of the recent rapid development of 3D measurement technology, we can apply 3D data information in surface defect detection to improve the recognition ability of defects. We propose a new convolutional network model to identify surface defects, and realize the feature depth fusion of 3D point cloud and 2D image in the model. In this work, we introduce an attention network to extract features from a 3D point cloud to generate a 2D attention mask. The high quality feature map is produced by combining the 2D attention mask with a 2D image. We further merge the attention network and the classification network into a single network. The attention network is used to analyze which part of the image should be more concerned by the classification network. Therefore, mutual learning of 2D data and 3D data is realized in the training process, which reduces the dependence on the number of samples and enhances the generalization performance of the model. Experiments on the defect dataset verify that our method can improve the classification effect of the model.

Digital speckle correlation (DSC) solves the problem of searching corresponding points between two images, and it shows great application potential in pattern-projection based fast 3D shape measurement, because only one shot is enough to retrieve the 3D structure. As DSC relies on analyzing the spatial intensity distribution of a subset in image with a given point, it is likely to get false correspondences in low quality DSC area such as the background, because the searching range is hard to locate. So it is still hard to use DSC to realize fast 3D shape measurement. To solve this problem, the gray standard deviation of the subset is designed to recognize and remove the low-quality DSC area, and the principle of epipolar geometry and disparity constraint are utilized to determine the searching range, so the correspondences can be obtained. Moreover, in order to enhance the robustness of this method, a connected region method based on neighboring pixels possessing similar disparity is proposed to remove mismatched points after establishing initial disparity map by correspondences. Once the disparity map is obtained 3D structure can be retrieved based on the triangulation principle. The experiment on reconstructing Gorky plaster statue is performed, verifying that the proposed method can substantially reduce mismatched points and achieve robust single frame 3D shape measurement.

Process signatures of the fusion area directly determine the quality of the part in Laser Powder Bed Fusion (LPBF). The geometric contour of the fusion area is one of the most important indicators of manufacturing quality. The accurate detection of the contour has been generating considerable interest. However, due to the complex operating condition in LPBF, the 2D images of the fusion area suffer from shortcomings such as poor contrast, high noise, and vary illumination. This makes the location of the contour extremely difficult for traditional detection methods. In this study, a robust contour detection method of the fusion area in LPBF is proposed. In order to raise the contrast of the contour, the phase image with clear contour details will be calculated from a series of fringe images with phase shift projected onto the fusion area. A phase-guided contour extraction method is conducted to accurately locate the center of contour which reduces significantly the impact of the severe manufacturing condition. Experimental results reveal that the proposed method can obtain the contours of the fusion area in a very short time, with higher accuracy and repeatability. In addition, it also holds the potential to be an effective way to monitor the geometric defects layer-wise.

A novel position measurement system, the so-called image grating system, is presented in this research paper. It features an adjustable measurement range, flexible standoff distance and in-line measurement capabilities. The developed position measurement system includes an image grating attached to the moving stage as the target feature and a line scan camera as the stationary displacement reader. By observing the position of the target feature in the image and applying subpixel image registration, the position of the moving stage can be determined. In order to improve the measurement efficiency, the computations for pattern correlation and subpixel registration are performed in the frequency domain. Calibration and error correction methods are also developed to compensate for the measurement error caused by optical distortion. Experimental data confirms the capability of the image grating technology of ±0.2 μm measurement accuracy within 25 mm measurement range. By applying different optics, the standoff distance and the measurement range can be customized for different precision measurement applications.

Two methods that used to measure the thickness of transparent plate were introduced in this paper. In conventional interferometry, multiple-surface interference fringes and the nonzero incidence angle complicated the calculation. In this study, the absolute thickness was obtained from the interferogram generated by two beams of coherent light reflected from the front surface and the rear surface of the transparent plate without reference surface. The thickness was obtained by analyzing light intensity of each point in the interferogram which varies sinusoidally with the wavelength in period method. While slope method figured out the mean thickness of whole surface with phase-shifting algorithm and least-square fitting algorithm. When the beam was perpendicular to the surface, the absolute thickness can be figured out with the refractive index n and λ₁, λ₂ in first technique. The results of simulation experiments indicated that the error in first technique was with sub micrometer, however the error of slope method was only a few nanometers.

The analysis and application of real-time and high-resolution images have attracted increasing attention of researchers, and are gradually increasing in artificial intelligence, civil engineering, remote sensing and other fields. Currently, array cameras are often used to obtain high resolution images. This study aims to research and design a transmission and storage scheme based on PCIE Peer-to-Peer transmission and SATA Array storage, which can meet the needs of high-speed data transmission and storage of industrial array camera. The whole design is divided into transmission and storage. Transmission uses Peer-to-Peer, high–bandwidth PCIE bus. The interface of the storage side is SATA. By defining and designing the external interface of SATA Host flexibly, we can realize a directly connection between the data to be stored and the SATA Host interface, which can save resource cost and meet the requirements of high transmission efficiency and strong scalability. Through PCIE Switch, the design transfers the data of multiple ports to the SoC directly for hard disk storage, which has the advantages of small size, fast speed and strong extensibility. This paper designed the Peer-to-Peer transmission and storage experiment of multiple channel. The feasibility of the design was fully demonstrated and obtained the relevant transmission performance parameters.

The information about the profiles of both surfaces of the transparent plate are contained in an interferogram. This information can be extracted by processing fringe patterns measured at different wavelengths. The conventional Fourier analysis applied to solve such problems with a set of a restricted number of the fringe patterns, otherwise this analysis is quite sensitive to the error of frequency drift and suffers from fringe patterns interference noise. This study proposes a method of frequency estimation to obtain profiles of surfaces of transparent plate. A series of fringe patterns obtained at different phase shift caused by wavelength changing are regarded as a set of overlapped sinusoidal signal. Using Total Least Squares method to find the frequency of different signal to attain the separation of interferogram. The simulation shows that the proposed method has the immunity from noise interference.

Interferometric techniques are very important in the metrology field, while the quality of the interferogram will directly affect the retrieval phase of the tested object. This paper presents a method to improve the quality of the interferogram including restoration of noise aliasing and moiré distortion by using the Gaussian Process Regression (GPR). Through choosing a suitable covariance function to describe the relationship between points and points in the fringe pattern, we build a Gaussian process regression model of interferogram, denoise the interferogram and improve the resolution at the same time. The treated interferogram can predict and compensate the part of the fringe distortion and enlarge the depth range of the interferometric measurement. Besides, with the resolution elevated of the hologram, a wider spectrum range can be obtained. In order to verify the possibility of this method, several simulations have been done, which showed a good performance in the enhancement of the quality of interferogram.

Cylindrical surface positioning task is defined as moving a camera to a certain pose with respect to cylindrical surface. To achieve this task, a fringe projection-based visual servoing method is proposed. First of all, phase shiftingbased fringe projection profilometry (FPP) is used to obtain 3D point cloud of the cylindrical surface. Then, the cylindrical axis is extracted by solving a least square optimization problem without constraints. Afterwards, a visual feature selection method is proposed to construct four features of six axis parameters and corresponding interaction matrix and control law are derived to move the camera to desired pose. Special circumstances when interaction matrix is highly decoupled is also discussed. Experiments on cylindrical axis fitting and cylindrical surface positioning task are performed. The results show the visual servo control method is feasible.

Point cloud has achieved great attention in 3D object classification, segmentation and indoor scene semantic parsing. In terms of face recognition, although image-based algorithm become more accurate and faster, open world face recognition still suffers from the influences i.e. illumination, occlusion, pose, etc. 3D face recognition based on point cloud containing both shape and texture information can compensate these shortcomings. However training a network to extract discriminative 3D feature is model complex and time inefficient due to the lack of large training dataset. To address these problems, we propose a novel 3D face recognition network(FPCNet) using modified PointNet++ and a 3D augmentation technique. Face-based loss and multi-label loss are used to train the FPCNet to enhance the learned features more discriminative. Moreover, a 3D face data augmentation method is proposed to synthesize more identity-variance and expression-variance 3D faces from limited data. Our proposed method shows excellent recognition results on CASIA-3D, Bosphorus and FRGC2.0 datasets and generalizes well for other datasets.

A newly developed flexible calibration algorithm for fringe projection profilometry system is presented in this paper. Previous studies have exploited images of spheres to calibrate the camera. It is shown in this paper that this approach can be improved to suit for the projector and ultimately achieve the overall calibration of FPP (Fringe Projection Profilometry) system. Taking the projector as a virtual camera, the images of sphere contour on the projectors plane can also be obtained through the phase information. The derivation and acquisition of intrinsic parameters for projector are just the same way used in the camera. In our algorithm, at least 3 images of sphere contour on both camera and projector are obtained to calculate the homography between these two views. Then the image of the sphere and its shadow on an induced plane settled in the back of the sphere are added to recover the epipolar geometry for the FPP system. Experimental results on real data are presented, which demonstrate the feasibility and accuracy achieved by our proposed algorithm.

In the field of precise 3D reconstruction, fringe pattern profilometry (FPP) is always regarded as the preferred method for it provides relatively higher accuracy. However, the phase acquisition process generally requires a sequence of images with different phase shift, which is rather time-consuming. Thus the application scenario of FPP is greatly limited and this has long been a bottleneck in practice. Although single-frame based phase retrieval algorithms like Fourier transform profilometry (FTP) has been proposed and extensively studied, they still suffer from relatively unbearable loss of accuracy. In response to this problem, we take advantage of the deep learning techniques and present a deep-learning based phase acquisition system in which the phase can be acquired by a single frame of fringe pattern image. The network is constructed according to the procedure of phase retrieval, which is trained by thousands of fringe pattern images with the phase data being known in advance. And it can predict more preciously the phase of a new fringe pattern map. Experiments illustrate the effect of our method which will be promising for practical use.

For disparity information acquisition tasks, phase-shift profilometry can achieve high disparity accuracy, but it is a stereo matching technique based on phase unwrapping. The phase unwrapping depends on the fringe pattern of multifrequency. Recent work also shows that deep learning can obtain disparity from a stereo pair of images, but it is difficult to obtain high accuracy. To tackle these problems, we propose a stereo matching method of obtaining high-accuracy disparity using a combination of the fringe pattern stereo matching network and the phase-shift method. First, the coarse disparity is obtained by using the fringe pattern stereo matching network, and then the wrapped phase map obtained by the 3 steps phase-shift method is used to optimize the coarse disparity to obtain a high-accuracy disparity map. This method rectifies the left and right fringe patterns in advance and eliminates the influence of the calibration parameters without loss of generality. It also avoids the challenge of phase unwrapping compared with phase-shift profilometry. We prove that the sinusoidal fringe pattern stereo matching can obtain a better coarse disparity effect than the stereo matching of the texture image, especially in the textureless area. Experiments show that high-precision disparity can be obtained with only three frames of high-frequency fringe patterns.

In order to extract the key points of weak texture regions in two-dimensional image matching, a linear multi-scale image enhancement matching algorithm based on image fusion technology is proposed in this paper. The algorithm mainly generates the weighted image of the original image according to the saturation, brightness, contrast and other measurement factors, enhances the distribution weight of weak texture, and makes more detail information fusion into the original image through the reconstruction of Gauss pyramid. The experimental results show that the algorithm effectively enhances the details of the weak texture region of the image, and can obtain more feature points for subsequent image matching.

Based on the processing mechanism of double-sided polishing machine and working mode, conducted intensive research, found that the motion state of the disc and pads can be simplified as a workpiece relative motion, and a complete mathematical model is built for the motion state of any point on the polishing disc. In view of the relationship among the workpiece’s motion characteristics, polishing process parameters and polishing effect, the computer is used to simulate the motion of the polishing disc relative to the workpiece in the state of steady motion. Taking the motion parameters as the control factor, by changing the ratio of different parameters, the different trajectory of the workpiece’s relative motion is obtained, and the regular pattern of the value of each factor on the motion trajectory distribution is explored. Finally, a set of parameters with the best grinding track uniformity and polishing effect were obtained through analysis and summary.

There are many approaches of frequency modulation to the optical signal in a single core fiber yet investigation of frequency modulation in a multicore fiber is not quite common at this time. We propose the new acousto-optic modulator using thin-layer ZnO transducer coated around the surface of a single mode multicore fiber (SM-MCF). The modulation frequencies from many hundred megahertz up to a few gigahertz are applied to investigate the characteristic of such a device by means of the theoretical calculations. Since the fiber has more than one core inside and some cores are not in the center, frequency shifting in different cores at the center and away from the center will be observed. Some parameters of the transducer, such as transducer length and thickness, and of the multicore fiber (MCF) structure will be varied to investigate the performance of the phase modulator. We found that the amplitude of modulation in different cores is various depending on the MCF structure. We believe this new device model can be applied in optical communication and sensors.

Adaptive optics (AO) systems are used to enhance the performance of optical systems. A classical AO system consists of the wavefront corrector with the wavefront sensor (WFS). Wavefront correctors are able to compensate for aberrations in real-time with the measured aberrations. Compared with traditional wavefront correctors, the major advantage of the magnetic fluid deformable mirror (MFDM) features large deformation strokes that can be easily up to more than 100μm both for the single actuator or inter-actuators. However, the measuring range of WFS is normally small, which could limit its usage in the applications with large aberrations. Considering the idea of taking full advantages of the MFDM’s stroke strengths and the limitations of the AO system with the WFS, this paper proposes a model-based wavefront sensorless control algorithm for the adaptive optics systems with magnetic fluid deformable mirror. Compared with the model-free wavefront sensorless AO systems, the model-based control algorithm for the wavefront sensorless AO systems features faster convergence without dropping into the local optima. The model-based control approach is developed based on a relationship between the second moments of the wavefront gradients and the far-field intensity distribution by taking Zernike polynomials as the predetermined bias functions, therefore, the unknown aberrations can be corrected without the wavefront measurement in the closed-loop AO control system. The control algorithm is evaluated in a wavefront sensorless AO system setup with a prototype MFDM, where a parallel laser beam with unknown aberrations is supposed to produce a focused spot on the CCD. Experimental results show that the model-based control method can effectively make the MFDM to compensate for unknown aberrations in an imaging system

Liquid mirror telescope (LMT) is a viable kind of telescope with a thin rotating mercury layer, which can generate excellent parabolic surface under the constant pull of gravity and a centrifugal acceleration. The cost of LMT is normally smaller than 1% of the cost of a traditional glass mirror telescope. However, the LMT cannot be tilted to observe larger field of sky due to the liquid property so that the field of view of LMT is very limit. In order to observe a larger field of the sky with LMT, the large off-axis aberrations must be compensated. Since the aberrations of a parabolic mirror increase rapidly with the increase of field angle, the classical correctors used in adaptive optics (AO) systems cannot correct the large off-axis aberrations of LMT when the field angles are significantly greater than 1 degree. In this paper, the magnetic fluid deformable mirror (MFDM) has been proposed as a new perspective to wavefront correction technology, which could produce a large stroke to compensate the large off-axis aberrations of LMT. The designed MFDM has a radius of 95 mm with 1141 actuators, which is able to correct the large off-axis aberrations of a 3-m f/4 LMT and permits the LMT to be operated at 10 degree off-axis observation from the zenith. The type and the order of off-axis aberrations generated by the liquid mirror telescope are first studied analytically and then the 3-m f/4 LMT operated at 10 degree off-axis observation is simulated in ZEMAX, where the off-axis aberrations and the Zernike coefficients of those aberrations are obtained from the simulation result. The required surface shape of MFDM can be calculated from the obtained Zernike coefficients of off-axis aberrations. Since the shape of the magnetic fluid surface is controlled by the combined magnetic field generated by a Maxwell coil and an array of micro-electromagnetic coils, the Maxwell coil and micro-electromagnetic coils are hence optimally designed to generate the required magnetic field. The correction performance of MFDM for the large off-axis aberrations of LMT is finally co-simulated by MATLAB, COMSOL and ZEMAX software. The simulation results show that the off-axis aberrations can be compensated with the designed MFDM and the Zernike coefficients of wavefront are substantially reduced.

Affected by voltage quantification, manufacture technology and environment temperature, the actual deflection accuracy and diffraction efficiency of liquid crystal optical phased arrays (LC-OPA) are in error with the ideal situation when the beam deflected. In this paper, we studied the method of improving the deflection performance of LC-OPA based on stochastic parallel gradient descent (SPGD) algorithm, and choose Strehl ratio (SR) as the performance evaluation function for simulation experiments. We analyzed the influence of the disturbance amplitude δ, the gain coefficient γ and the number of periodic electrodes N on the performance optimization of the SPGD algorithm in the LC- OPA beam. Draw the conclusion: When the number of periodic electrodes N is within a certain range, appropriate adjustment of the disturbance amplitude δ and the gain coefficient γ can achieve better optimization effects, and the larger the deflection angle, the better the optimization effect. When the number of periodic electrodes N is 4, the amplitude of disturbance δ is 0.0009, and the gain coefficient γ is 0.1, the ideal optimization effect of SR of 0.82 can be achieved, which provides a theoretical basis for improving the large-angle deflection precision and diffraction efficiency of LC-OPA.

Transformation optics (TO) is a new method to design metamaterials that can manipulate electromagnetic fields. Different from the traditional TO technique which is mostly based on the solid metamaterials with a limited range of tunability, a novel transformation optofluidics (TOF) method is proposed to manipulate the light path by changing the streamlines of the flow in a circular bounded domain. A dipole flow model was built for the first time to analytically calculate the streamlines of a liquid core/liquid cladding (L²) configuration inside the domain. Experiment show that the light paths agree well with the theoretical models and have a large range of tunability for any optical source-sink pair locations and flow rate ratio of two cladding fluids.

An ultra-compact all-optical AND/NAND logic switch using symmetric two micro-ring resonators (MRRs) are theoretically proposed under optical pump-probe configuration. Two pump pulses are employed to modulate two MRRs respectively. The simulation verified the proposed design which possesses extinction ratios (ER) of 12.3 dB at ultra-low pump power of 1.82mW.

Quantum dot (QD) lasers are playing an important role in high-speed optical communications and high-temperature sensing applications due to stable operation at high temperature. We propose here performance analysis of QD laser fabricated using standard photolithography and wet etch process. An InAs-GaAs quantum dot laser is fabricated and characterized for 0.948 V operating potential developed across the device and light-current characteristics exhibiting threshold current density (J_th) of 56A/cm² per QD layer in both pulse and CW mode of operation. The slope efficiency of – 0.182 mW/A is measured in pulse mode. The optical power ranges up to 63 mW in pulse mode and 45 mW in CW operation at 800 mA. An analysis has been carried to estimate the threshold at different temperature exploiting quasiFermi levels and distribution of current density over the QD layers and confinement layers.

We present a new quantitative phase imaging method on the basis of the novel camera named quantitative phase imaging camera with a weak diffuser (QPICWD). It measures object under low-coherence quasi-monochromatic illumination via examining the deformation of the speckle intensity pattern. The speckle deformation can be analyzed by means of ensemble average of geometric flow method, realizing high resolution distortion field by using the transport of intensity equation (TIE). There are some applications for the proposed new design including nondestructive optical testing of microlens array with nanometric thickness. Since the proposed QPICWD needs no modification of the common bright-field microscope, it may promote QPI as a useful tool for subcellular level biological analysis.

Digital image correlation is an effective way for accurate dimensional measurements with merits of non-contact and high precision abilities. Accurate calibration for the binocular stereo vision system is critical. A simple calibration method has been proposed in this study with the use of an inertial measurement unit (IMU) on each imaging station. As the IMU is aligned with the optical axis of the camera, the orientation of the camera is known. This helps in determining the rotation matrix of the extrinsic parameter of the camera based on the epipolar constraint relationship. The experimental results show that the proposed method has good accuracy and flexibility

2D-displacement measurement with real time image processing is developed. The target of camera image is a lattice pattern drawn on the paper sheet. The range of measurement depends only on the size of target sheet, so that high resolution power as well as large measuring range are realized with proposal method. The histogram distribution of the image of the lattice pattern is calculated, and the position of the grid lines are detected from the peak positions of the distribution. By continuously performing this detection, it is possible to calculate the movement of the image. From the target grid lines spacing (in mm) and the grid lines spacing on the image (in pixels), the calculation of the displacement is done automatically. The features of this method are that real-time measurement can be performed with high-speed processing, measurement can be easily performed simply by setting the grid line interval (mm), and measurement can be performed with sub-pixel accuracy. In this research, the measurement accuracy and the tolerance to poor image quality of the proposed method were evaluated. As a result, it has been shown that the position of the grid line can be detected with sub-pixel accuracy even in a poor-quality image. As an application of this method, the relative displacement between the base and tested building was obtained with the measurement during 3-dimensional vibration tests.

Birefringence measuring equipment currently used has either a high-sampling-rate or large-area measurement without high-spatial resolution. A birefringence distribution measurement of 10 kilopixels or more with high-spatial resolution at a sampling rate of 10 kHz or more has yet to be achieved. To develop the elemental technology to achieve this, this study proposes preliminary equipment, namely, a circular polariscope with a polarized laser, high-speed camera, and photoelastic modulator (PEM). The light source used was a 5-mW He–Ne laser with a wavelength of 632.8 nm; the light-receiving element was a high-speed camera with a photographing speed of 200 kHz, and harmonic analysis of the light intensity was achieved with a PEM. To demonstrate the possibility of high-speed measurement with the proposed equipment, the birefringence of a variable-wave plate was measured using one pixel of the high-speed camera. As a result, the maximum error of the measured value was 5.3% in the birefringence range of 10–20 nm of the specimen, 7.9% between 20–40 nm, and 4.0% between 40–60 nm. To show that measurement is also possible when the imaging range is expanded, the birefringence distribution in the area of 60 × 60 µm of the 40-nm wave plate was measured using 8 × 8 pixels of the high-speed camera. This method returned a smooth monotonously varying birefringence distribution close to 40 nm. The result shows that expanding the 8×8 pixels to 10 kilopixels can achieve the aforementioned research goals.

Depth information perception of unstructured scene images is an important problem for applications using computer vision. This paper proposes a method based on deep learning combined with self-attention mechanism to reason the depth information of unstructured indoor targets, which effectively solves the problem of blurred image detail and insufficient layering in depth information reasoning in unstructured scenes. First, the deep learning-based encoder-decoder model is trained to learn the depth information of indoor scenes on large 3D datasets. The trained model has good results for general structured indoor scenes. Secondly, the soft self-attention mechanism is used to obtain the disparity information between the upper and lower sequences of the input image, by which the depth map obtained in the first step is corrected to enhance the accuracy of depth. Finally, in order to get clear objects with obvious boundaries in the depth response map, the nearest neighbor regression is used to correct the contour of the objects. The experimental results show that the proposed method has very good depth information reasoning ability for indoor unstructured scenes. Through depth information reasoning, the obtained objects have obvious texture structure, strong geometric features, clear contour edges and delicate layers, and also the misleading of deep information reasoning in reflective and highlight areas is eliminated.

The study of defect dynamics is an important problem in the field of non-destructive testing, crack propagation and fracture mechanics. Optical interferometric techniques are extensively used for this purpose because of their non-invasive behaviour and full field operation. The fringe patterns obtained from these techniques serve as good indicators for finding defects. In dynamic defect analysis, a large number of fringe patterns are captured and processed. The regions where the fringe density varies significantly are classified as defects. Thus, a fast, reliable and robust algorithm for identifying the rapid variations of fringe density is required. In this paper, we propose a graphics processing unit (GPU) assisted space frequency method based on windowed Fourier spectrum analysis for processing the dynamically varying fringe patterns. The main advantage of this approach is high computational efficiency achieved using GPU computing framework. The performance of the proposed method is demonstrated using 100 simulated fringe patterns, each of size 2048 x 2048 pixels. This large data stack was efficiently processed using the proposed method within only a minute, and thus, the proposed method offers the feasibility of high speed defect analysis. The practical application of the proposed method is explored by processing the fringe patterns obtained from the propagation of micron sized defects in an experimental configuration based on common-path diffraction phase microscopy setup.

In a conventional fringe projection profilometry (FPP) consisted of a camera and a projector, just one-sided 3D data of the tested object can be obtained by a single-shot measurement. Therefore, tools such as turntables are commonly used to obtain 360-degree 3D point cloud data of objects. However, this method requires multiple measurements and point cloud registration, which is time consuming and laborious. With the help of two planar mirrors, this paper proposes an improved system that captures fringe images from three different perspectives including one real camera and two virtual cameras. The information of the planar mirrors (i.e., the mirror calibration) is achieved by artificially attaching the featured pattern to the surface of the mirrors. Using the calibration parameters of the planar mirrors, the 3D point cloud data obtained by the virtual cameras can be converted into the real coordinate system, thereby reconstructing the full-surface 3D point cloud data with relative roughness. Finally, an improved ICP algorithm is introduced to obtain high-precision 360-degree point cloud data. The experimental results demonstrate that with the help of the mirrors, our system can obtain high-quality full-surface 360-degree profile results of the measured object at high speed.

Structural crack is an important factor which causes failure of reinforced concrete bridges. In this work, automatic detection and dimensional measurement of concrete bridge crack are researched, for improving technical level and efficiency of concrete bridge state assessment. Images containing crack features are first recognized using information entropy characteristics of intensity clustering, for promoting efficiency and robustness of rough crack localization based on proportional segmentation. After the features are refined at sub-pixel level, their actual dimensions are accurately measured employing a cross structured light system. Experiments show that the problems such as high misjudgment, low efficiency and poor accuracy in the existing technologies are preliminarily addressed; the proposed method performs well in crack detection and measurement using concrete bridge structure images.

3D reconstruction of point cloud data is the research focus at present, but there isn’t a universal 3D reconstruction method for point cloud data which is scattered topology structure. At the same time, 3D reconstruction method of point cloud data also exist many problem, such as: 3D modeling efficiency is low, 3D reconstruction model exist holes, 3D model isn’t quite true. To solve these problems in 3D reconstruction of point cloud data, this paper provides a 3D reconstruction method for laser spiral scanning point cloud, the 3D reconstruction method which has high efficiency, true model and retains model details can solve the problem of 3D reconstruction .To verify the effectiveness of algorithm, this paper choose a set of spiral point cloud which will be sorted and optimized, finally these point cloud data have been transferred into 3D expected solid model which will provide a good basic for future usage of point cloud data.

Zinc oxide is a preferred choice for several optoelectronic applications owing to their unique properties, such as wider band gaps combined with high exciton binding energies. A zinc oxide thin film was grown on glass substrates through sol-gel depositing method followed by heat treatments. We prepared the zinc oxide thin films using zinc acetate dihydrate, 2-methoxy ethanol and diethanolamine as zinc alkoxide precursor, solvent and sol stabilizer respectively. Structural and optical characterizations were carried out that included X-ray diffraction, Atomic force microscopy, Profilometry and UV-Visible spectrophotometry. A coplanar configuration of device has been chosen where the structure has Zinc oxide thin film on which metal contacts of 100 nm thickness were deposited onto the films via thermal evaporation. A two probe source meter was used for I-V measurements in dark environment. I-V measurements have been done for various concentrations of biomolecules (Vitamin B6). It is found that there are variations in current for increasing concentrations.

The measuring technique combining phase-shifting algorithm and Gray-code light has been widely used in threedimensional (3D) shape measurement for static scenes owing to its high robustness and anti-noise ability. However, it is challenging for this method to realize a high-speed shape measurement using fewer patterns. Because of the object motion and the defocus of the projector, phase unwrapping errors occur easily on the boundaries of adjacent Gray-code words. In existing methods, median filtering or extra patterns projecting were used to overcome this challenge. In this paper, two robust Gray-code coding strategies have been proposed for the same purpose. By recoding the traditional Gray codes in temporal and spatial domains respectively, cyclic complementary Gray-code (CCGC) patterns and shifting Gray-code (SGC) patterns are designed. Both of these two coding strategies can obtain two sets of decoding words whose boundaries are stagger for one wrapped phase. To avoid using the decoding words on the edge, different decoding codes are used depending on the range of phase value. So the robust and simple phase unwrapping can be achieved without projecting extra patterns. High-quality 3D results of multiple randomly moving objects with sharp edges verified the proposed methods’ feasibility and validity

In fringe projection profilometry, using denser fringes can improve the measurement accuracy. In real-time measurement situations, the number of the fringe pattern is limited to reduce motion-induced errors, which, however, poses more difficulties for the absolute phase recovery from dense fringes. In this paper, we propose a stereo phase matching method that takes advantage of the high-accuracy of denser fringes and the high-efficiency of using only two different frequencies of fringes. The phase map is divided into several sub-areas and in each sub-area, the phase is unwrapped independently. The correct matched pixel is easily selected from the distributed candidates in different sub-area with the help of geometry constraints.

Three-dimensional (3D) registration or matching is a crucial step in 3D model reconstruction. In this work, we develop a real-time 3D point cloud registration technology. Firstly, in order to achieve real-time 3D data acquisition, the stereo phase unwrapping method is utilized to eliminate the ambiguity of the wrapped phase, assisted with the depth constraint strategy without projecting any additional patterns or embedding any auxiliary signals. Then we implement SLAM-based coarse registration and ICP-based fine registration to match the point cloud data after the rapid identification of two-dimensional (2D) feature points. In order to improve the efficiency of 3D registration, the relative motion of the measured object at each coarse registration is quantified, through which only one fine registration is performed after several coarse registrations. The experiment shows that, the complex model can be registered in real time to reconstruct its whole 3D model with our method.

In this paper, we propose a fast panoramic 3D shape measurement technique based on the multi-view system with plane mirrors. Fringe projection profilometry (FPP), as an active 3D measurement technique based on structured light and triangulation, has been one of the most promising methods for measuring dynamic scenes, due to its inherent property of non-contact, full-field, high-precision, and high efficiency. However, for acquiring the 360-degree 3D information of the tested object with complex surfaces, multiple measurements from different perspectives and the complicated registration algorithms need to be implemented, which are time-consuming and low efficiency that limits the potential application of FPP. To solve this problem, by introducing plane mirrors into the traditional FPP system, we develop a mirror-assisted panoramic measurement system, which can capture deformed fringe images of the measured object from three different perspectives simultaneously including a real camera and two virtual cameras realized by plane mirrors. In addition, a robust calibration method is proposed to easily calibrate the mirror, which can be used to convert 3D data obtained from real and virtual perspectives into a common world coordinate system. Then, for low-modulation fringe regions, they are further corrected based on the proposed phase compensation technique. Finally, these proposed techniques constitute a complete computational framework that allows achieving a fast, high-accuracy, and panoramic 3D reconstruction results with high completeness.

Phase-to-height mapping is indispensable part of three-dimensional (3D) shape measurement system based on phase analysis, which guarantees the accuracy of 3D reconstruction. In this paper, a real time 3D shape reconstruction method based on dual-frequency composite grating projection and phase-height lookup table is proposed. In this method, a reference plane is moved with a known interval along the measurement depth direction to establish a mapping lookup table between the wrapped phase of dual-frequency composite grating and the corresponding spatial height pixel by pixel respectively. The actual experimental results show that the reconstruction accuracy of this method is better than that of the traditional phase-to-height quadratic fitting method. Finally, combining the high performance parallel computation of GPU, the real time 3D shape reconstruction with the speed of 60 fps and the resolution of 1152*800 pixels is realized.

Stereoscopic display technology has a high sense of presence and can bring unparalleled stereoscopic enjoyment to the audience, which requires stereoscopic glasses, helmet display and other auxiliary visual tools in that greatly limits its application. Auto-stereoscopic display technology (especially based on lenticular lens ) enables the audience to feel the visual impact brought by stereoscopic images freely and clearly with the naked eye in multiple positions within the larger perspective, thus greatly promoting the development and application of stereoscopic display technology. In this paper, an integrated imaging technique based on lenticular lens (88 inches) and projection equipment is introduced. The parameters of lenticular lens grating are calculated firstly, then, we use the 3Ds Max software to acquire the parallax images of the object, integrating all the parallax image pixels together to obtain an image with parallax by using Matlab program. The integrated parallax image is matched by the optical transmission characteristics of the lenticular lens. Experiment show that, the integrated imaging technique based on lenticular lens (88 inches) and projection equipment can display a good stereo image and realize super large-size, true color, dynamic and smooth parallax display. A 3D display by using a large lenticular lens and a projector is achieved in this paper.

Phase unwrapping is one of the key steps for fringe projection profilometry (FPP)-based 3D shape measurements. Conventional spatial phase unwrapping schemes are sensitive to noise and discontinuities, which may suffer from low accuracies. Temporal phase unwrapping is able to improve the reliability but often requires the acquisition of additional patterns, increasing the measurement time or hardware costs. This paper introduces a novel phase unwrapping scheme that utilizes composite patterns consisting of the superposition of standard sinusoidal patterns and randomly generated speckles. The low-rankness of the deformed sinusoidal patterns is studied. This is exploited together with the sparse nature of the speckle patterns and a robust principal component analysis (RPCA) framework is then deployed to separate the deformed fringe and speckle patterns. The cleaned fringe patterns are used for generating the wrapped phase maps using the standard procedures of phase shift profilometry (PSP) or Fourier Transform profilometry (FTP). Phase unwrapping is then achieved by matching the deformed speckle patterns that encode the phase order information. In order to correct the impulsive fringe order errors, a recently proposed postprocessing step is integrated into the proposed scheme to refine the phase unwrapping results. The analysis and simulation results demonstrate that the proposed scheme can improve the accuracy of FPP-based 3D shape measurements by effectively separating the fringe and speckle patterns.

The growing availability of counterfeit drugs has greatly increased the need for track and trace of drugs through the supply chain. Although numerous methods such as tagging, labelling, and marking are available for identifying and authenticating drug packages, none are available for the contents. A method is presented for directly identifying individual medicine tablets without any markings or additives. A lighting system is used to capture an image of a tablet’s micro-scale surface bumps, which is then used as the "fingerprint" of that tablet. Since plain unmarked tablets have no macroscopic (humanvisible) feature, the orientation of the fingerprint image cannot be controlled during capture. Tablets are thus identified by geometric invariant image matching using Fourier-Mellin phase features. Experimental results show that the proposed image matching algorithm enables accurate and robust identification of numerous plain tablets.

Fringe projection profilometry (FPP) has attracted considerable interests for addressing the challenge of measuring three-dimension (3D) shapes of moving objects. Compared with phase shift profilometry (PSP) which requires the capture of multiple fringe patterns and is thus only suitable for static objects, Fourier transform profilometry (FTP) is less sensitive to motion-induced errors. However, FTP is prone to the influence of background lights and variations of the surface reflectivity, which may result in less accurate measurements. There are studies aimed to reduce the measurement errors with FTP using more sophisticated processing of the fringe patterns. However, existing works focus on schemes based on single images and the correlation of the dynamic 3D shapes is largely unexplored. In this work, we present a new method that refines FTP-based dynamic shape measurements. Assuming 3D rigid movements of the targets, we propose to utilize knowledge of the motion parameters and combine the multiple height maps obtained from several FTP measurements after compensating the motion effect. Approaches for automatically combining the height information are studied. It is observed that the measurement accuracy can be improved using the proposed method and the influence due to ambient lights and reflectivity variations can be suppressed. Computer simulations are performed to verify the effectiveness of the proposed method. The proposed method can also be integrated into other FPP systems to improve the performance for dynamic object measurements.

With the rapid development of computer technology, image measurement technology has been widely used because of its non-contact, high precision and other advantages. In recent years, potable consumer devices like mobile phone, VR/AR device, tablet computer etc. become more and more popular. The number of high precision small workpieces has increased exponentially. There is an urgent need for the high accuracy and high speed measurement approach for the quality control of the small workpieces. Due to the contradiction between accuracy and field of view, the existing image measuring instruments are not sufficient, and it is difficult to meet the needs of high precision and high efficiency measurement. In this paper, several aspects of high-precision image measurement system are explored, including hardware system construction, double side telecentric lens design, high-precision template matching technology, system calibration, sub-pixel feature extraction and image segmentation algorithm. According to the actual demand, a high precision detection system is integrated, a high-precision image rapid measurement system for small workpieces (size < 70mm) is designed and developed. The accuracy of 2um and speed of 7000UPH are obtained which can meet the industrial requirements.

The monoamine neurotransmitter dopamine-containing cells originate at the brain’s mesencephalic-diencephalic junction and project to several forebrain targets. Within the central nervous system, dopamine plays a crucial role in reward, motivation and motor control. In the periphery, it is involved in renal vasodilation, natriuresis, and diuresis. Dysfunction in dopaminergic neurotransmission has been implicated in several neurological and psychiatric conditions including mood disorders, schizophrenia, Parkinson's disease, and obsessive-compulsive disorder. It is imperative to understand the property of such a key brain molecule. Therefore, here, we use a continuous-wave (CW) laser closed-aperture (CA) Zscan technique to unravel the nonlinear property of dopamine at physiological condition (pH~7.4). Interestingly, we observe that dopamine shows nonlinearity when exposed to various input laser intensity. We attribute the origin of observed nonlinearity majorly governed by saturated atomic absorption mechanism along with insignificant contribution from thermal lensing effect. Our approach is simple and robust, and our observations have opened up new avenues for investigating dopaminergic processes by utilizing its nonlinear property. This study is of immense importance to researchers in the fields of nonlinear optics, biophysics, and neuroscience.