This PDF file contains the editorial “Relevance and Interest” for OE Vol. 49 Issue 03

A videogrammetric system is proposed for monitoring the 3-D deformation time history of a metal sheet surface during welding, which could not be achieved by traditional displacement sensors. Two commercial-grade digital video cameras are used for image acquisition. The major algorithms of the videogrammetric process such as target recognition, stereo matching, 3-D reconstruction, and target tracking, are discussed in detail. An improved self-calibration method based on a planar pattern is proposed and verified. Precision evaluation experiments prove that the proposed system could achieve an accuracy of 0.05 mm. Three welding deformation surveying experiments using different metal sheets are conducted to validate the performance of the videogrammetric system and the obtained data are compared with results from linear variable differential transducers. The agreement between videogrammetric and conventional results confirms the availability and reliability of the proposed videogrammetric system for monitoring dynamic welding deformation of metal sheets.

The color rendering index (CRI) has been shown to have deficiencies when applied to white light-emitting-diode-based sources. Furthermore, evidence suggests that the restricted scope of the CRI unnecessarily penalizes some light sources with desirable color qualities. To solve the problems of the CRI and include other dimensions of color quality, the color quality scale (CQS) has been developed. Although the CQS uses many of elements of the CRI, there are a number of fundamental differences. Like the CRI, the CQS is a test-samples method that compares the appearance of a set of reflective samples when illuminated by the test lamp to their appearance under a reference illuminant. The CQS uses a larger set of reflective samples, all of high chroma, and combines the color differences of the samples with a root mean square. Additionally, the CQS does not penalize light sources for causing increases in the chroma of object colors but does penalize sources with smaller rendered color gamut areas. The scale of the CQS is converted to span 0-100, and the uniform object color space and chromatic adaptation transform used in the calculations are updated. Supplementary scales have also been developed for expert users.

The calibration of the cameras used in close-range photogrammetry is usually performed using auxiliary elements with known geometry and/or dimensions, through one or several photographs of elements with geometrical restrictions, which enable the calculation of the different parameters needed. This research suggests an improvement in these procedures through the use of one or several laser meters. The method is based on the use of calibration pillars in a laboratory, in which the cameras and laser meters subject to calibration are fixed. The cameras are calibrated by determining the relative positions of all the devices at the same time, which enables the application of the algorithm designed for hybrid laser-camera systems used for measuring in civil engineering and robotics. For this purpose, photographs and measurements are taken by laser meters over a moving object of unknown geometry and dimensions.

A direct method of determining second-order derivatives of displacement (curvature and twist) using two-channel double-aperture digital shearography is presented. Spatial carrier fringes are incorporated inside the speckle using a double-aperture mask in a two-channel experimental setup. Two sets of slope phase maps are generated that are either shifted in the x direction for curvature measurement or in the y direction for twist measurement. Experimental results are presented to verify the validity of the proposed method.

Recently, sandwich holography was proposed in heat transfer studies. This technique can provide the temperature gradient without the need to calculate the temperature map and then numerically differentiate it; also phase extraction and phase unwrapping are avoided. A numerical simulation was used to assess the performance of the technique. This investigation shows the ability of the method to obtain the convective coefficient h with an accuracy of about 6%. The measurement algorithm is also relatively robust with respect to noise.

A method for testing the 90-deg error of dihedral angles of glass cubes is proposed. The test beam of a Fizeau interferometer enters the cube and is retroreflected by a dihedral angle to interfere with the reference beam. The angle between different regions of the retroreflective wavefront can be obtained using a phase-shifting interferometer. The relation between subwavefronts and the dihedral angle error is deduced, so the latter can be calculated. It does not need any extra auxiliary optical components. In the experiment, a glass cube is tested on the phase-shifting interferometer, and its four dihedral angle errors in the same principal section are obtained. The results obey the angle sum of a quadrangle principle with a tolerance of 0.04″. Moreover, the result is validated by another method, as the differences between them are less than 0.06″.

An antenna-coupled detector's directional properties can be verified by measuring its angular radiation pattern. At infrared frequencies, this pattern can be measured by rotating the device while illuminating it with a laser beam. An accurate radiation pattern can be measured only if the device is coaligned with the axis of rotation and the focus of the laser beam. In the alignment procedure presented, the device is rotated to various angles and the distance along the orthogonal axis from the current device position to the laser beam is measured by maximizing its response. Calculations based on these distances provide the new location of the device, which will coalign it with the axis of rotation and the focus of the laser beam. The successful alignment enables accurate radiation pattern measurements.

Displaying of images on monitors actually samples them. When a sinusoidal image is displayed on a monitor, a frequency that is much smaller than the frequency of the original image might be seen, which appears as a moiré fringe. Characteristics of this fringe depend on the geometry of the monitor's pixel lattice and the frequency of the displayed image. By changing the image frequency, one can access a moiré fringe of infinite period. In this situation, there is a simple relation between the image period and the monitor's pixel period. The estimated error in determining the number of the pixels of a monitor is a small fraction of 1 pixel.

We propose a new technique to extract overdrive (OD) values that are indispensable to improve response characteristics of liquid-crystal displays. We show the relation among an OD value (D_OD), a previous frame data (D_PF), and a current frame data (D_CF) can be expressed very well by a third-order polynomial. To make the implementation of the OD technology to be simple, we propose to create a base line that is expressed by the third-order equation and to linearly shift it according to D_PF. Our proposed method does not need the large size lookup tables (LUTs), whereas the conventional OD technology requests huge LUTs. Thus, our method can be easily implemented by very small circuits, which enables a low-cost solution. Only six measurements in our method are sufficient to obtain OD values of all the transition, whereas the conventional one wants 256 measurements. We investigate the best position of the base line and show how small the deviation from optimum values is. We prove that the proposed OD technology enables a low-cost implementation, high productivity, and high performance.

We demonstrate a wavelength-independent tunable liquid crystal (LC) polarization rotator using two nematic LC retarders for the spectral range from 450 to 1000 nm and wider. The first LC device with tunable retardation determines the rotation, while the second acts as an LC variable quarter-wave plate. Integration with tunable optical filters produces a modality for great potential in spectropolarimetry.

The design and performance of an all-solid-state Nd:YVO₄ laser, transversely pumped by a single 20-W (at 808 nm) diode with no coupling optics, are presented. The prototype, which is devised to be the source of a micro-LIDAR station, is very simple, easy to align, compact, and stable. The key element is a roof prism as the end mirror of the laser cavity, which is used to symmetrize the effects of the thermal distortion and the inhomogeneity of the population inversion distribution. Typical numbers are 4.2-W cw with a slightly astigmatic (3:2) homogeneous spot and a divergence of 0.5 mrad. The protoype is also tested in the active Q-switching mode, providing pulses 50-ns full width at half maximum (FWHM) at 14 KHz, 3.5 W average. Frequency doubling external to the cavity in a nonoptimized configuration provides 700 mW at 532 nm.

A single biconical fiber taper is a simple and low-cost yet powerful sensor. With a distinct strength in refractive index (RI) sensing, biconical tapered fiber sensors can find their place in handheld sensor platforms, especially as biosensors that are greatly needed in health care, environmental protection, food safety, and biodefense. We report doubling of sensitivity for these sensors with two passes through the tapered region, which becomes possible through the use of sensitive and high-dynamic-range photodetectors. In a proof-of-principle experiment, we measured transmission through the taper when it was immersed in isopropyl alcohol-water mixtures of varying concentrations, in which a thin gold layer at the tip of the fiber acted as a mirror enabling two passes through the tapered region. This improved the sensitivity from 0.43 dB/vol % in the single-pass case to 0.78 dB/vol % with two passes through the taper. The refractive index detection limit was estimated to be ~1.2×10^-5 RI units (RIU) and ~0.6×10^-5 RIU in the single- and double-pass schemes, respectively. We predict that further enhancement of sensitivity may be achieved with a higher number of passes through the taper.

We demonstrate the formation of a fundamental soliton from a higher order soliton in a silicon waveguide if the two-photon absorption (TPA) parameter is judiciously chosen. We also report the effect of TPA on soliton-soliton interaction in a silicon waveguide.

We propose the design method of fiber parametric wavelength converters based on dispersion-flattened photonic crystal fibers (PCFs) with two zero-dispersion wavelengths (ZDWs). Analytical expressions of the optimum signal frequency and maximal pump tuning range are deduced. By our method, the tuning ranges can be considerably broadened with a relatively low pump power and short fiber. This is because the fourth-order dispersion coefficient of two ZDW PCFs can be 1-2 orders of magnitude larger than those of one ZDW fiber and are effectively utilized to compensate the linear phase mismatch due to the second-order dispersion, resulting in a low phase mismatch for a widely tunable pump. To exemplify the effectiveness of our method, a PCF based on lead-silicate glasses with two ZDWs spaced 127-nm apart is presented. Numerical simulations show that based on this PCF a transparent wavelength conversion with a 117-nm pump tuning range can be achieved with only a 3.7-m-long fiber and 0.532 W pump power.

We study the traffic grooming problems in wavelength-division multiplexing (WDM) networks with arbitrary topologies (such as the ring or mesh WDM network), aiming to improve the throughput and minimize the blocking probability in the network. The grooming problem is formulated as an optimization problem in the network, and the optimizing solution consists of three parts of design: the virtual topology, the route of the lightpaths, and the assignment of the wavelengths to the lightpaths. An evolutionary algorithm, named adaptive immune evolutionary algorithm was proposed. The feature of the proposed algorithm is in introducing the adaptive parameters so as to avoid premature convergence and enhance searching efficiency toward its solution. Experimental results and comparison with two well-known algorithms show that the proposed algorithm has better resource utilization for random traffic grooming in WDM networks.

We introduce a new preemptive scheduling technique for next-generation optical burst switching (OBS) networks considering the impact of cascaded wavelength conversions. It has been shown that when optical bursts are transmitted all optically from source to destination, each wavelength conversion performed along the lightpath may cause certain signal-to-noise deterioration. If the distortion of the signal quality becomes significant enough, the receiver would not be able to recover the original data. Accordingly, subject to this practical impediment, we improve a recently proposed fair channel scheduling algorithm to deal with the fairness problem and aim at burst loss reduction simultaneously in OBS environments. In our scheme, the dynamic priority associated with each burst is based on a constraint threshold and the number of already conducted wavelength conversions among other factors for this burst. When contention occurs, a new arriving superior burst may preempt another scheduled one according to their priorities. Extensive simulation results have shown that the proposed scheme further improves fairness and achieves burst loss reduction as well.

Quaternary inverters are the fundamental building blocks of multivalued flip-flops (MVFFs). A novel all-optical quaternary universal inverter circuit with the help of a semiconductor optical amplifier-assisted Sagnac switch is proposed and described. This circuit exploits the polarization properties of light. Different logical states are represented by different polarization states of light. A terahertz optical asymmetric multiplexer-based gate plays an important role here. Numerical simulation results confirming the described method are given. An all-optical circuit for a MVFF (quaternary) with the help of our proposed quaternary universal inverter is also designed, and simulation results are presented.

A novel practical method for detection of underwater no-reflection object is introduced. We adopt a Faraday isolator and a Glan prism as the signal isolation and extraction subsystem, which can strengthen the returned signal by using the phase conjugation characteristic of stimulated Brillouin scattering and interrupt other reflected light with small aperture. Qualitatively, a Fabry-Pérot étalon is used to determine the presence or absence of the underwater object by observing the absence of the stimulated Brillouin scattering light corresponding interference rings. Quantitatively, we use a photodiode to receive and an oscilloscope to display the returned signal to determine the interval that can be used to calculate the object's depth. Thus, we can observe the signals in the time domain and the frequency domain simultaneously. Some numerical calculation results concerning the system's longitudinal resolution are given and the corresponding influences are discussed. A 10-m-long water pipe is used in the experiments. An underwater no-reflection object located at a maximal depth of 8 m is detected and the results agree well with the real condition.

We investigate performance of a convex nonquadratic (CNQ) spline regularization method applied to limited-angle tomography reconstruction. Since limited-angle data lack projections over a certain range of view angles, they produce poor reconstructions with streak artifacts and geometric distortions. To obtain a good solution, a feasible prior that can eliminate or reduce artifacts and distortions is necessary. The CNQ prior used in this paper is expressed as a linear combination of the first- and the second-order spatial derivatives and applied to a CNQ penalty function. To determine a solution efficiently, we use the fast globally convergent block sequential regularized expectation maximization algorithm. Our experimental results demonstrate that the hybrid CNQ spline prior outperforms conventional nonquadratic priors in eliminating limited-angle artifacts.

Multibiometrics can obtain a higher accuracy than the single biometrics by simultaneously using multiple biometric traits of the subject. We note that biometric traits are usually in the form of images. Thus, how to properly fuse the information of multiple biometric images of the subject for authentication is crucial for multibiometrics. We propose a novel image-based linear discriminant analysis (IBLDA) approach to fuse two biometric traits (i.e., bimodal biometric images) of the same subject in the form of matrix at the feature level. IBLDA first integrates two biometric traits of one subject into a complex matrix and then directly extracts low-dimensional features for the integrated biometric traits. IBLDA also enables more information to be exploited than the matching score level fusion and the decision level fusion. Compared to linear discriminant analysis (LDA), IBLDA has the following advantages: First, it can overcome the small sample size problem that conventional LDA usually suffers from. Second, IBLDA solves the eigenequation at a low computational cost. Third, when storing the scatter matrices IBLDA will not bring as heavy a memory burden as conventional LDA. We also clearly show the theoretical foundation of the proposed method. The experiment result shows that the proposed method can obtain a high classification accuracy.

Conventional object-detection and localization approaches require extensive time to process the sliding background windows, which are not like the object at all. Global context of the subwindow gives access to alleviate such problems. In addition, many patch-based approaches often fail to search the patches at the correct locations and local context can help to resolve that. We propose an object-detection framework, which is top down and simple to implement. It combines global contextual features, local contextual features, and local appearance features in a coarse-to-fine cascade, which enables fast detection. The three features mentioned above play different roles in the process of object detection, and the representation with rich information makes detection robust and effective. The proposed approach shows satisfactory performance in both speed and accuracy.

We propose a moving objects segmentation method for color image sequences based on the piecewise constant Mumford-Shah model (also known as the C-V model) solving by the semi-implicit additive operator splitting (AOS) scheme, which is unconditionally stable, fast, and easy to implement. The method first uses the Gaussian mixture model for background modeling and then subtracts the background to obtain the moving regions that are the handling objects of our method. As a result of the introduction of the AOS scheme, we could use a rather large time step and still maintain the stability of the evolution process. Additionally, the method can easily be parallelized because the AOS scheme decomposes the equations into a sequence of one-dimensional (1-D) systems. The experimental results demonstrate that under real moving objects video tests, the AOS scheme accelerates the evolution of the curve and significantly reduces the number of iterations, and also demonstrates the validity of our method.

A digital photogrammetry measurement system (XJTUDP) is developed in this work, based on close range industry. Studies are carried out on key technologies of a photogrammetry measurement system, such as the high accuracy measurement method of a marker point center based on a fitting subpixel edge, coded point design and coded point autodetection, calibration of a digital camera, and automatic image point matching algorithms. The 3-D coordinates of object points are reconstructed using colinear equations, image orientation based on coplanarity equations, direct linear transformation solution, outer polar-line constraints, 3-D reconstruction, and a bundle adjustment solution. Through the use of circular coded points, the newly developed measurement system first locates the positions of the camera automatically. Matching and reconstruction of the uncoded points are resolved using the outer polar-line geometry of multiple positions of the camera. The normal vector of the marker points is used to eliminate the error caused by the thickness of the marker points. XJTUDP and TRITOP systems are tested on the basis of VDI/VDE2634 guidelines, respectively. Results show that their precision is less than 0.1 mm/m. The measurement results of a large-scale waterwheel blade by XJTUDP show that this photogrammetry system can be applied to industrial measurements.

A scale-invariant feature transform (SIFT)-based particle filter algorithm is presented for joint detection and tracking of independently moving objects in stereo sequences observed by uncalibrated moving cameras. The major steps include feature detection and matching, moving object detection based on multiview geometric constraints, and tracking based on particle filter. Our contributions are first, a novel closed-loop mapping (CLM) multiview matching scheme proposed for stereo matching and motion tracking. CLM outperforms several state-of-the-art SIFT matching methods in terms of density and reliability of feature correspondences. Our second contribution is a multiview epipolar constraint derived from the relative camera positions in pairs of consecutive stereo views for independent motion detection. The multiview epipolar constraint is able to detect moving objects followed by moving cameras in the same direction, a configuration where the epipolar constraint fails. Our third contribution is a proposed dimensional variable particle filter for joint detection and tracking of independently moving objects. Multiple moving objects entering or leaving the field of view are handled effectively within the proposed framework. Experimental results on real-world stereo sequences demonstrate the effectiveness and robustness of our method.

Resolution of continuous-wave (CW) terahertz scanning image is limited by many factors among which the aperture effect of finite focus diameter is very important. We have investigated the factors that affect terahertz (THz) image resolution in details through theory analysis and simulation. On the other hand, in order to enhance THz image resolution, Richardson-Lucy algorithm has been introduced as a promising approach to improve image details. By analyzing the imaging theory, it is proposed that intensity distribution function of actual THz laser focal spot can be approximatively used as point spread function (PSF) in the restoration algorithm. The focal spot image could be obtained by applying the pyroelectric camera, and mean filtering result of the focal spot image is used as the PSF. Simulation and experiment show that the algorithm implemented is comparatively effective.

We propose a steganographic method that is based on side match vector quantization (SMVQ). The secret data are encrypted and then embedded in an SMVQ-decompressed image. In the decoding process, both the hidden secret and the original SMVQ code can be reconstructed without any error. Experimental results demonstrate that the proposed method provides a high hiding capacity and acceptable stego-image quality, to an extent comparable to a well-known SMVQ-based reversible steganographic method.

Two-dimensional face-recognition techniques suffer from facial texture and illumination variations. Although 3-D techniques can overcome these limitations, the reconstruction and storage expenses of 3-D information are extremely high. We present a novel face-recognition method that directly utilizes 3-D information encoded in face fringe patterns without having to reconstruct 3-D geometry. In the proposed method, a digital video projector is employed to sequentially project three phase-shifted sinusoidal fringe patterns onto the subject's face. Meanwhile, a camera is used to capture the distorted fringe patterns from an offset angle. Afterward, the face fringe images are analyzed by the phase-shifting method and the Fourier transform method to obtain a spectral representation of the 3-D face. Finally, the eigenface algorithm is applied to the face-spectrum images to perform face recognition. Simulation and experimental results demonstrate that the proposed method achieved satisfactory recognition rates with reduced computational complexity and storage expenses.

Homography can be estimated from corresponding points, lines, or textures. But in some scenarios these features are not always available. As a supplement, the newly developed contour-based method is presented, which can be used to estimate the homography between any two planar contours of an image sequence. The proposed method improves the random sampling consensus (RANSAC) method into an iterative form. In the iterations, the random sample process of RANSAC is constrained by the previous iteration results. It reduces the blind sample process and ensures fast convergence speed. The experimental results demonstrate that the proposed method is effective.

Automatic counting of passengers is very important for both business and security applications. We present a single-camera-based vision system that is able to count passengers in a highly crowded situation at the entrance of a traffic bus. The unique characteristics of the proposed system include, First, a novel feature-point-tracking- and online clustering-based passenger counting framework, which performs much better than those of background-modeling-and foreground-blob-tracking-based methods. Second, a simple and highly accurate clustering algorithm is developed that projects the high-dimensional feature point trajectories into a 2-D feature space by their appearance and disappearance times and counts the number of people through online clustering. Finally, all test video sequences in the experiment are captured from a real traffic bus in Shanghai, China. The results show that the system can process two 320×240 video sequences at a frame rate of 25 fps simultaneously, and can count passengers reliably in various difficult scenarios with complex interaction and occlusion among people. The method achieves high accuracy rates up to 96.5%.

We describe a new pose-estimation algorithm via integration of the strength in both empirical mode decomposition (EMD) and mutual information. While mutual information is exploited to measure the similarity between facial images to estimate poses, EMD is exploited to decompose input facial images into a number of intrinsic mode function (IMF) components, which redistribute the effect of noise, expression changes, and illumination variations as such that, when the input facial image is described by the selected IMF components, all the negative effects can be minimized. Extensive experiments were carried out in comparisons to existing representative techniques, and the results show that the proposed algorithm achieves better pose-estimation performances with robustness to noise corruption, illumination variation, and facial expressions.