This PDF file contains the front matter associated with SPIE Proceedings Volume 9216,, including the Title Page, Copyright information, Table of Contents, Authors, Introduction (if any), and Conference Committee listing.

Light emitting diodes (LEDs) can be selected to target the wavelengths absorbed by plantlets, enabling the users to customize the wavelengths of light required for maximum production. The primary purpose of this experiment was to test the effect of different ratios of red to blue LEDs on tomato plantlets photosynthetic action spectrum. Four light treatments including: red LED (100%) and three ratios of red (661 nm) to blue (449 nm) light (5:1, 10:1 and 19:1) at 60 umol m^-2 s^-1 for this study. The tomato plantlets cultured without blue light showed a three and half-fold decrease in photosynthesis rate. The highest photosynthetic action spectrum was observed at 10:1 but was not significantly difference from the 5:1 and the lowest action spectrum was observed at 100% red LED light. The tomato plantlets grown without the blue light showed a single-fold increase in plantlet height but were not significantly different from the 10:1 red to blue LED light. This research will allow for improved selection of LED lighting for plant tissue culture.

In fluorescence molecular tomography (FMT), the fluorophore distribution is reconstructed using the diffuse-light measurements obtained from the rotating source-detector pairs placed on the boundary of the tissues. Owing to the intensity attenuation of light when it propagates through tissues, the sensitivity of measurements deteriorates quickly with increased depth. Thus the inconsistent contrast of reconstructed fluorophores located at different depths is a major challenge in FMT. As a spatially variant regularization method, the adaptive support driven reweighted L1-minimization (ASDR-L1) algorithm is proposed here for depth compensation in FMT. ASDR-L1 is a modification of the restarted L1 regularization-based nonlinear conjugate gradient (re-L1-NCG) algorithm previously proposed by our laboratory. In ASDR-L1, the original L1-minimization problem is replaced by a sequence of weighted L1-minimization subproblems with spatially updated weights applied to the adaptive support estimate. Like re-L1-NCG, ASRDR-L1 adopts the restarted strategy in each outer iteration, which contributes to the adaptive support estimate. The updated weights for the next iteration spatially depend on the current solution. In the support estimate, spatially updated weights mean different regularization parameters for different locations. A large regularization parameter in the weighted L1-minimization subproblem makes the results concentrate on a small number of large values, whereas a small regularization parameter tends to make the values be evenly distributed. Thus depth compensation in FMT is achieved through the iteratively updated weights. Simulation experiments are conducted to confirm the feasibility of ASDR-L1. Through ASDR-L1, the reconstructed contrast between two identical fluorophores located at different depths is increased from 1:0.43 to 1:0.96.

This research introduces an automatic technique designed for the digital restoration of the damaged parts in historical documents. For this purpose an imaging spectrometer is used to acquire a set of images in the wavelength interval from 400 to 1000 nm. Assuming the presence of linearly mixed spectral pixels registered from the multispectral image, our technique uses two lattice autoassociative memories to extract the set of pure pigments conforming a given document. Through an spectral unmixing analysis, our method produces fractional abundance maps indicating the distributions of each pigment in the scene. These maps are then used to locate cracks and holes in the document under study. The restoration process is performed by the application of a region filling algorithm, based on morphological dilation, followed by a color interpolation to restore the original appearance of the filled areas. This procedure has been successfully applied to the analysis and restoration of three multispectral data sets: two corresponding to artificially superimposed scripts and a real data acquired from a Mexican pre-Hispanic codex, whose restoration results are presented.

This paper proposes a method to recover the pulse signal with the theory of lock-in amplifier and calculates the oxygen saturation. The pulse signal is obtained based on the method of Photoplethysmography (PPG). We use a LED as the light source and a photoelectric diode as the receiver to get a measured pulse wave. Because the pulse wave obtained by this method is easily disturbed by motion artifact, we use an electrocardiogram (ECG) signal to aid PPG measurement. Firstly, the ECG signal is processed by the Fast Fourier Transform (FFT) and get the heart rate. Secondly, with the value of heart rate, a typical noise free pulse waveform can be constructed. Finally, we use it as a reference input to get a recovered pulse wave by the theory of lock-in amplifier. Thus, the value of oxygen saturation can be calculated accurately through two recovered pulse waveforms of red (660nm) and infrared (940nm) light. Some volunteers were tested. The correlation coefficient between the experimental data and the data provided by a reference instrument is 0.98, proving that this method has high reliability and utility in motion.

Thermal therapy (or hyperthermia) is one of the effective operations for tumor treating and curing. As tumor tissues are more susceptible to heat than normal tissues, in thermal therapy operations, temperature on operation area is a crucial parameter for optimal treating. When the temperature is too low, the tumor tissues cannot be killed; otherwise, the temperature is too high, the operation may damage normal tissues around the tumor. During thermal therapy operation, the heating power is normally supplied by high-frequency EM field, so traditional temperature sensors, such as thermal couples, thermistors, cannot work stably due to EM interference. We present a multi-function endoscope optical fiber temperature sensor system. With this sensor setup based on principle of fluorescence life time, the temperature on operation point is detected in real time. Furthermore, a build-in endoscope centers in the fiber sensor, thus the operation area can be viewed or imaged directly during the operation. This design can navigate the operation, particularly for in vivo operations. The temperature range of the sensor system is 30°C-150°C, the accuracy can achieve to 0.2°C. The imaging fiber buddle is constituted of more than 50k fibers. As the sensor probe is very thin (around 4 mm in diameter), it can also be assembled inside the radiofrequency operation knife. With the presented sensor system in clinic operation physicians can check the temperature in the operation point and view the operation area at the same time.

Light interactions with matter is of remarkable complexity. An adequate modeling of global illumination is a vastly studied topic since the beginning of computer graphics, and still is an unsolved problem. The rendering equation for global illumination is based of refraction and reflection of light in interaction with matter within an environment. This physical process possesses a high computational complexity when implemented in a digital computer. The appearance of an object depends on light interactions with the surface of the material, such as emission, scattering, and absorption. Several image-synthesis methods have been used to realistically render the appearance of light incidence on an object. Recent global illumination algorithms employ mathematical models and computational strategies that improve the efficiency of the simulation solution. This work presents a review the state of the art of global illumination algorithms and focuses on the efficiency of the solution in a computational implementation in a graphics processing unit. A reliable system is developed to simulate realistics scenes in the context of real-time object recognition under different lighting conditions. Computer simulations results are presented and discussed in terms of discrimination capability, and robustness to additive noise, when considering several lighting model reflections and multiple light sources.

Smart lighting solutions based on imaging sensors such as webcams or time-of-flight sensors suffer from rising privacy concerns. In this work, we use low-cost non-imaging color sensors to measure local luminous flux of different colors in an indoor space. These sensors have much higher data acquisition rate and are much cheaper than many o_-the-shelf commercial products. We have developed several applications with these sensors, including illumination feedback control and occupancy-driven lighting.

We present results from a prototype CMOS camera system implementing a multiple sampled pixel level algorithm (“Last Sample Before Saturation”) to create High-Dynamic Range (HDR) images that approach the dynamic range of CCDs. The system is built around a commercial 1280 × 1024 CMOS image sensor with 10-bits per pixel and up to 500 Hz full frame rate with higher frame rates available through windowing. We analyze imagery data collected at room temperature for SNR versus photocurrent, among other figures of merit. Results conform to expectations of a model that uses only dark current, read noise, and photocurrent as input parameters.

We describe an advanced computational imaging system with an optical architecture that enables simultaneous and dynamic pupil-plane and image-plane coding accommodating several task-specific applications. We assess the optical requirement trades associated with custom and commercial-off-the-shelf (COTS) optics and converge on the development of two low-cost and robust COTS testbeds. The first is a coded-aperture programmable pixel imager employing a digital micromirror device (DMD) for image plane per-pixel oversampling and spatial super-resolution experiments. The second is a simultaneous pupil-encoded and time-encoded imager employing a DMD for pupil apodization or a deformable mirror for wavefront coding experiments. These two testbeds are built to leverage two MIT Lincoln Laboratory focal plane arrays – an orthogonal transfer CCD with non-uniform pixel sampling and on-chip dithering and a digital readout integrated circuit (DROIC) with advanced on-chip per-pixel processing capabilities. This paper discusses the derivation of optical component requirements, optical design metrics, and performance analyses for the two testbeds built.

The Advance Radiographic Capability (ARC) at the National Ignition Facility (NIF) is a laser system designed to produce a sequence of short pulses used to backlight imploding fuel capsules. Laser pulses from a short-pulse oscillator are dispersed in wavelength into long, low-power pulses, injected in the NIF main laser for amplification, and then compressed into high-power pulses before being directed into the NIF target chamber. In the target chamber, the laser pulses hit targets which produce x-rays used to backlight imploding fuel capsules. Compression of the ARC laser pulses is accomplished with a set of precision-surveyed optical gratings mounted inside of vacuum vessels. The tilt of each grating is monitored by a measurement system consisting of a laser diode, camera and crosshair, all mounted in a pedestal outside of the vacuum vessel, and a mirror mounted on the back of a grating inside the vacuum vessel. The crosshair is mounted in front of the camera, and a diffraction pattern is formed when illuminated with the laser diode beam reflected from the mirror. This diffraction pattern contains information related to relative movements between the grating and the pedestal. Image analysis algorithms have been developed to determine the relative movements between the gratings and pedestal. In the paper we elaborate on features in the diffraction pattern, and describe the image analysis algorithms used to monitor grating tilt changes. Experimental results are provided which indicate the high degree of sensitivity provided by the tilt sensor and image analysis algorithms.

We present a pedestrian localization technique that does not need infrastructure. The proposed angle-only measurement method needs specially manufactured shoes. Each shoe has two CMOS cameras and two markers such as LEDs attached on the inward side. The line of sight (LOS) angles towards the two markers on the forward shoe are measured using the two cameras on the other rear shoe. Our simulation results shows that a pedestrian walking down in a shopping mall wearing this device can be accurately guided to the front of a destination store located 100m away, if the floor plan of the mall is available.

The National Ignition Facility (NIF) utilizes 192 beams, four of which are diverted to create the Advanced Radiographic Capability (ARC) by generating a sequence of short laser pulses. This ARC beam after being converted to X-rays will act as a back lighter to create a radiographic movie and provide an unprecedented insight into the imploding dynamics and serve as a diagnostic for tuning the experimental parameters to achieve fusion. One such beam is the centering beam of the pre-amplifier module which due to a split path obstructs the central square alignment fiducials. This fiducial is used for alignment and also as reference for the programmable spatial shaper (PSS) system. Image processing algorithms are used to process the images and calculate the position of various fiducials in the beam path. We discuss the algorithm to process ARC split beam injector (SBI) centering images with partial fiducial information.

In this paper, we proposed parallel processing method of 2 step wave field projection method using GPU. In the first step, 2D projection of wave field for 3D object is calculated by radial symmetric interpolation (RSI) method to the reference depth, and then in step 2 it is translated toward depth direction using Fresnel transformation. In each step, the object points are divided into small groups and processed in each CUDA cores in parallel. Experimental results show that proposed method is 5901 times faster than Rayleigh-Sommerfeld method for 1 million object points and full HD SLM resolution.

We provide an efficient method of using Morlet wavelets for transforming a hologram and reconstructing parts of a scene based on the position of viewer by using a sparse set of Morlet transformed coefficients. We provide a design of a Morlet wavelet and explain an efficient discretization method for the application of view-dependent representation systems. Results are provided based on the numerical reconstruction, and it is shown that view- dependent representation along with Morlet wavelets form a good starting step for compressing holographic data for next generation 3DTV applications.

Parallel-aligned liquid crystal on silicon (PA-LCoS) displays have become the most attractive spatial light modulator device for a wide range of applications, due to their superior resolution and light efficiency, added to their phase-only capability. Proper characterization of their linear retardance and phase flicker instabilities is a must to obtain an enhanced application of PA-LCoS. We present a novel polarimetric method, based on Stokes polarimetry, we have recently proposed for the measurement of the linear retardance in the presence of phase fluctuations. This can be applied to electrooptic devices behaving as variable linear retarders, and specifically to PA-LCoS. The method is based on an extended Mueller matrix model for the linear retarder containing the time-averaged effects of the instabilities. We show experimental results which validate the predictive capability of the method. The calibrated retardance and phase fluctuation values can then be used to estimate the performance of the PA-LCoS device in spatial light modulation applications. Some results will be given.

Transmission of optical beams with phase front vorticity through relevant distances in optical fibers poses a problem of time-dependent intermodal interference with random complex coefficients. In this paper we propose a method for compensation of interference between LP-modes, propagating through the optical fiber. To implement optical-domain modal filtering, reconfigurable diffractive optical element matched with particular modes is considered. Such an element may be encoded as phase-only hologram by means of SLM. With this approach modes can be separated spatially in the compensating diffractive element far field and handled independently with corresponding complex coefficients. Efficiency of the proposed method is confirmed by computer simulation results.

The goal of this intelligent transportation systems work is to improve the understanding of the impact of carbon emissions caused by vehicular traffic on highway systems. In order to achieve this goal, this work implements a pipeline for vehicle segmentation, feature extraction, and classification using the existing Virginia Department of Transportation (VDOT) infrastructure on networked traffic cameras. The VDOT traffic video is analyzed for vehicle detection and segmentation using an adaptive Gaussian mixture model algorithm. The morphological properties and histogram of oriented features are derived from the detected and segmented vehicles. Finally, vehicle classification is performed using a multiclass support vector machine classifier. The resulting classification scheme offers an average classification rate of 86% under good quality segmentation. The segmented vehicle and classification data can be used to obtain estimation of carbon emissions.

This work presents a baseline estimation method in flame spectra based on artificial intelligence structure as a neural network, combining robust statistics with multivariate analysis to automatically discriminate measured wavelengths belonging to continuous feature for model adaptation, surpassing restriction of measuring target baseline for training. The main contributions of this paper are: to analyze a flame spectra database computing Jolliffe statistics from Principal Components Analysis detecting wavelengths not correlated with most of the measured data corresponding to baseline; to systematically determine the optimal number of neurons in hidden layers based on Akaike's Final Prediction Error; to estimate baseline in full wavelength range sampling measured spectra; and to train an artificial intelligence structure as a Neural Network which allows to generalize the relation between measured and baseline spectra. The main application of our research is to compute total radiation with baseline information, allowing to diagnose combustion process state for optimization in early stages.

In this work, we propose electro-optical nonlinear delayed feedback systems (NDFS) for optical secure communications using VCSEL for the first time. Its optical output can perform more sensitive chaotic dynamics by varying only a few mA of injection current range resulting in very significant charges of VCSEL’s operation conditions from threshold to maximum rating. This enables us to vary chaotic output dynamically by a slight difference of initial values in NDFS. We have proposed a chaos synchronization system using two identical NDFS’s of VCSEL, and realized chaos synchronization by optical injection. As a result of experiment the correlation coefficient up to about 0.88 was obtained. Moreover, by varying the delay time and feedback gain in the parameters of NDFSs, we have confirmed that the variations of these parameters may affect variations of correlation.

The most effective recent approaches to processing and restoration of images and video are ones that flexibly adapt themselves to the content of these signals. These high performance methods have come about through the convergence of several powerful ideas from different science and engineering disciplines. Examples include Moving Least Square (from computer graphics), the Bilateral Filter and Anisotropic Diffusion (from computer vision), Boosting and Spectral Methods (from Machine Learning), Non-local Means and Bregman Iterations (from Applied Math), Kernel Regression and Iterative Scaling (from Statistics). These approaches are deeply connected; and in this talk, I will present a framework for understanding many common underpinnings of these ideas. This has led us to new insights and algorithms, yielding both deeper theoretical analysis, and state of the art results in practice.

In recent work, the propagation of a profiled optical beam through an open-loop acousto-optic Bragg cell was examined using a transfer function formalism. The device was also studied under closed-loop via intensity feedback, and shown to exhibit more extended chaotic band responses, thereby potentially increasing the dynamic range and parameter sensitivities of any applied signal and the device operation respectively. In this paper, simple low- to mid-RF signals (periodic waveforms and low BW audio) are transmitted through the closed-loop system and the resulting encryption and recovery at the receiver are examined especially from the perspective of overall robustness of the system.

A novel evolution scheme from legacy TDM-PON to the next generation WDM-PON with DPSK/ASK orthogonal modulation is proposed. The new WDM-PON is added into the existing PON infrastructure and coexisting with the current TDM-PON. To eliminate any change requirement for the existing TDM-PON, DPSK is applied for WDM-PON downstream. Meanwhile, upstream remodualtion is applied to achieve colorless ONU in WDM-PON. The application of DPSK/ASK reduces both crosstalk from coexisting and remodulation. The experiment results show the crosstalk is very little. Good performance is achieved for both unchanged coexisting TDM-PON and WDM-PON upstream signals in our proposed scheme.

Since around 1979, the operation of an acousto-optic Bragg cell under positive first-order feedback via amplification and delay in the loop has been studied extensively by several groups [1-3]. In recent work, the analysis of the nonlinear dynamics (NLD) of the system was extended to include bistable maps and Lyapunov exponents, and application of the chaos for signal encryption and decryption for uniform plane waves. The present work originated with the problem of a variable photodetector aperture opening relative to the first-order light. This potentially complex problem is simplified by assuming instead a variable feedback gain ( β ~ (t)), which leads to considerably different NLD. This paper examines initially the NLD versus the (DC) bias voltage for different variable- β ~ conditions, including slow and fast rates of change of the gain with time in relation to the feedback delay. It is found that the response depends critically on the rate of rise of the feedback gain, and also that the resulting chaotic regimes are generally significantly different from those for fixed values of β ~ . We have generated constant feedback gain and the variable feedback gain (t) chaos characteristics of the hybrid A-O network. Chaos as an equivalent carrier has been used to encrypt messages for both fixed and variable β ~ . The transmitted signal is detected from the encrypted carrier using a heterodyne method, using a slave Bragg cell with matched keys to generate local chaos followed by a low pass filter and a phase inverter. Results between variable- and fixed-gain systems are compared in terms of advantages and disadvantages.

In the paper we have proposed recognition of object by RCS diagrams method. For modeling the scattering field of 3D objects on underlying surface we had use widely known FDTD method. We have used for distance function in developing method conjugation indices with so-called support plane, is formed within feature vectors of recognition class. We have given the results of recognition experiments with three different methods: support vector method, correlation method with the average class vector and a new support plane method.

The continuous linear canonical transforms is known to describes wave field propagation through paraxial (quadratic phase) optical systems. Digital algorithms to numerically calculate the LCT are therefore important in modelling field propagation through first order optical systems and are also of interest for many purely digital signal processing applications. Significantly the continuous LCTs are unitary, but discretization can destroy this property resulting in a loss of conservative properties. Previously we presented a sufficient condition on the sampling rates chosen during discretization to ensure that digital implementations of the 1D and 2D separable LCTs were unitary. In this paper we extend our analysis to discuss the cases of the 2D non-separable LCT which are used to describe non-orthogonal, nonaxially symmetric and anamorphic systems. We also examine the consequences of ours results.

De-noising of terahertz (THz) pulsed spectroscopy (TPS) data is an essential problem, since a noise in the TPS system data prevents correct reconstruction of the sample spectral dielectric properties and to perform the sample internal structure studying. There are certain regions in TPS signal Fourier spectrum, where Fourier-domain signal-to-noise ratio is relatively small. Effective de-noising might potentially expand the range of spectrometer spectral sensitivity and reduce the time of waveform registration, which is an essential problem for biomedical applications of TPS. In this work, it is shown how the recent progress in signal processing in wavelet-domain could be used for TPS waveforms de-noising. It demonstrates the ability to perform effective de-noising of TPS data using the algorithm of the Fast Wavelet Transform (FWT). The results of the optimal wavelet basis selection and wavelet-domain thresholding technique selection are reported. Developed technique is implemented for reconstruction of in vivo healthy and deseased skin samplesspectral characteristics at THz frequency range.

In this paper, the problems of recognition of individual particle images in the volume of optical medium conditioned upon their coherent superposition are described. To evaluate the efficiency of methods of particle image recognition, a typical problem of analysis of the intensity distributions formed by laser radiation scattered on suspended particles in a volume of an optical medium is considered. As a result of applying of the method of statistical accounting of particle images, based on the edge-point linking and thresholding technique, normalized density distributions of particles in the image plane are obtained. Evaluation of the performance of applied recognition method for individual particle images is conducted using correlation analysis to assess the quality of obtained images.

Human visual system (HVS) can visualize all the brightness levels of the scene through visual adaptation. However, the dynamic range of most commercial digital cameras and display devices are smaller than the dynamic range of human eye. This implies low dynamic range (LDR) images captured by normal digital camera may lose image details. We propose an efficient approach to high dynamic (HDR) image fusion that copes with image displacement and image blur degradation in a computationally efficient manner, which is suitable for implementation on mobile devices. The various image registration algorithms proposed in the previous literatures are unable to meet the efficiency and performance requirements in the application of mobile devices. In this paper, we selected Oriented Brief (ORB) detector to extract local image structures. The descriptor selected in multi-exposure image fusion algorithm has to be fast and robust to illumination variations and geometric deformations. ORB descriptor is the best candidate in our algorithm. Further, we perform an improved RANdom Sample Consensus (RANSAC) algorithm to reject incorrect matches. For the fusion of images, a new approach based on Stationary Wavelet Transform (SWT) is used. The experimental results demonstrate that the proposed algorithm generates high quality images at low computational cost. Comparisons with a number of other feature matching methods show that our method gets better performance.

Functional Near infrared spectroscopy (fNIRS) is a newly noninvasive way to measure oxy hemoglobin and deoxy hemoglobin concentration changes of human brain. Relatively safe and affordable than other functional imaging techniques such as fMRI, it is widely used for some special applications such as infant examinations and pilot’s brain monitoring. In such applications, fNIRS data sometimes suffer from undesirable movements of subject’s head which called motion artifact and lead to a signal corruption. Motion artifact in fNIRS data may result in fallacy of concluding or diagnosis. In this work we try to reduce these artifacts by a novel Kalman filtering algorithm that is based on an autoregressive moving average (ARMA) model for fNIRS system. Our proposed method does not require to any additional hardware and sensor and also it does not need to whole data together that once were of ineluctable necessities in older algorithms such as adaptive filter and Wiener filtering. Results show that our approach is successful in cleaning contaminated fNIRS data.

We analyze the effects of coloring of a beam traversing a light-scattering medium. Spectral investigation of the effects of coloring has been carried out using a solution of liquid crystal in a polymer matrix (PDLC). It is shown that the result of coloring of the beam at the output of the medium depends on the magnitudes of the phase delays of the singly forward scattered partial signals. We consider the influence of interference coloring effect on the transmission scattering and spatial-frequency filtering of the radiation which has passed through the PDLC.

To determine the relative pose between an object and a single camera using correspondences between 3D feature points of the object and their corresponding 2D projections in the image, this paper proposes a target’s pose measurement algorithm based on the bundle adjustment method. This iterative algorithm can be divided into two steps: first, a reliable initial pose is computed by using only three non-collinear points; second, the optimal rotation and translation matrix of the target is estimated based on the bundle adjustment method. Experiments on simulated data and real data show that this method can get high precision with its rotation angles error within 20 arc-second and the translation error within 20 micron in ideal occasions.

This paper represents the investigation results of spatial chaotization of optical field scattered by liquid crystals during phase transition liquid – liquid crystal under electric field. Two stochastic parameters of the field, namely, Lyapunov's maximal index and correlation exponent was chosen for this study. It has been established that maximum variances of phase inhomogeneities of the nematic liquid crystal corresponds to maximum fluctuations of order parameter under temperature of phase transition liquid – liquid crystal. Was found that analysis of the radiation field scattered during the phase transition process the liquid-liquid crystal allows to accurately determine the phase transition temperature and voltage of forming Williams’s domains.

A wide range of chemical compositions are possible to design photopolymers. These materials are also appealing for diffractive and holographic applications due to their capability to modulate the refractive index and/or the thickness when illuminated. Some of the most interesting applications for photopolymers are the optical data storage, security systems, surface relief photo-embossing, diffractive and refractive optical elements, holographic elements, solar concentrators, optical detectors and hybrid optoelectronic 3-D circuitry. Looking for an optimized chemical composition for each application many different photopolymers compositions may be needed enabling a variety of materials properties: materials with low or high rates of monomer diffusion, low or high values of shrinkage, long or short length of polymer chains and low or high light absorption. In parallel many models are presented in order to predict the photopolymers recording and the post exposure evolution. In this work we use one of these experimentally checked models to study the influence of the material characteristics in the final diffractive optical element recorded in the material. We study the changes in the surface relief and in the refractive index in order to understand the importance of each material property in the final diffractive optical element recorded.

This work presents a framework designed for the Mexican Sign Language (MSL) recognition. A data set was recorded with 24 static signs from the MSL using 5 different versions, this MSL dataset was captured using a digital camera in incoherent light conditions. Digital Image Processing was used to segment hand gestures, a uniform background was selected to avoid using gloved hands or some special markers. Feature extraction was performed by calculating normalized geometric moments of gray scaled signs, then an Artificial Neural Network performs the recognition using a 10-fold cross validation tested in weka, the best result achieved 95.83% of recognition rate.

A new azimuthally stable polarimetric method for processing of microscopic images of optically anisotropic structures of different biological layers histological sections is proposed. A new model of phase anisotropy definition of biological tissues by using superposition of Mueller matrices of linear birefringence and optical activity is proposed. The matrix element M₄₄ has been chosen as the main information parameter, which value is independent of rotation angle of both sample and probing beam polarization plane.

The model of Mueller-matrix description of mechanisms of optical anisotropy typical for polycrystalline films of liquor - optical activity, birefringence, as well as linear and circular dichroism - is suggested. Within the statistical analysis of such distributions the objective criteria of differentiation of films of liquor from the dead you people different times were determined. From the point of view of probative medicine the operational characteristics (sensitivity, specificity and accuracy) of the method of Mueller-matrix reconstruction of optical anisotropy parameters were found and its efficiency in another task - diagnostics of diseases of internal organs of rats was demonstrated.

Optical correlation technique of cement particle size distribution determining is described. It is based on transverse coherent function measuring using a polarization transverse shearing interferometer. It is shown that set of particles with random form can be substituted with set of spherical particles. This result was obtained by simulation of different particles sets with different forms and orientations. The proposed technique of data processing decreases dependence of the result on interferometer noise, emission source intensity fluctuations and difference of refractive index magnitudes of different cement particles. Described technique allows fast and reliable determining the size distribution function of cement particles.

We consider the analysis of the spectra of the dynamic signal optical range by the methods of acousto-optics at light diffraction by a traveling acoustic wave excited by a periodic sequence of radio pulses with a rectangular envelope and a linear variation of the instantaneous frequency. The procedure of the linear approximation of the acousto-optic interaction is described. Acousto-optic interaction is thought of as a bilinear transformation of the spectral components, which are radio signal and optical radiation. It is shown that from the bilinear spectral transformation ensue relations, describing the spectral processing or radio or optical signal as a result of diffraction on grating structure formed by traveling acoustic wave. The problem of spectrum analysis of optical signals by optical spectral device based on acoustooptic tunable filter is considered separately. An expression allowing to investigating in detail the possibility of such an optical spectral device is obtained.

Congenital red-green color vision deficiency is one of the most common genetic disorders. A previously printed set of pseudoisochromatic plates (KAMS test, 2012) was created for individual discrimination threshold determination in case of mild congenital red-green color vision deficiency using neutral colors (colors confused with gray). The diagnostics of color blind subjects was performed with Richmond HRR (4th edition, 2002) test, Oculus HMC anomaloscope, and further the examination was made using the KAMS test. 4 male subjects aged 20 to 24 years old participated in the study: all of them were diagnosed with deuteranomalia. Due to the design of the plates, the threshold of every subject in each trial was defined as the plate total color difference value ΔE at which the stimulus was detected 75% of the time, so the just-noticeable difference (jnd) was calculated in CIE LAB DeltaE (ΔE) units. Authors performed repeated discrimination threshold measurements (5 times) for all four subjects under controlled illumination conditions. Psychophysical data were taken by sampling an observer’s performance on a psychophysical task at a number of different stimulus saturation levels. Results show that a total color difference value ΔE threshold exists for each individual tested with the KAMS pseudoisochromatic plates, this threshold value does not change significantly in multiple measurements. Deuteranomal threshold values aquired using greenish plates of KAMS test are significantly higher than thresholds acquired using reddish plates. A strong positive correlation (R=0.94) exists between anomaloscope matching range (MR) and deuteranomal thresholds aquired by the KAMS test and (R=0.81) between error score in the Richmond HRR test and thresholds aquired by the KAMS test.

Spoof attack by replicating biometric traits represents a real threat to an automatic biometric verification/ authentication system. This is because the system, originally designed to distinguish between genuine users from impostors, simply cannot distinguish between a replicated biometric sample (replica) from a live sample. An effective solution is to obtain some measures that can indicate whether or not a biometric trait has been tempered with, e.g., liveness detection measures. These measures are referred to as evidence of spoofing or anti-spoofing measures. In order to make the final accept/rejection decision, a straightforward solution to define two thresholds: one for the anti-spoofing measure, and another for the verification score. We compared two variants of a method that relies on applying two thresholds – one to the verification (matching) score and another to the anti-spoofing measure. Our experiments carried out using a signature database as well as by simulation show that both the brute-force and its probabilistic variant turn out to be optimal under different operating conditions.

Main information limitation of digital holograms is quantity of pixels. Necessity of spatial separation of informative diffraction order from undesired diffraction orders leads to additional reduction of quantity of resolved elements in reconstructed object. Eight methods of numerical suppression of undesired diffraction orders were compared. Under numerical testing using computer generated Fresnel holograms it was found that good quality of reconstructed images is provided by five out of eight methods. Digital Fresnel holograms were recorded and used for further methods comparison. Selection of field of frequencies zeroing method showed best results. Slightly worse results demonstrated median and Gauss filtering methods.

Method of increase of quality of computer generated kinoforms is proposed. It is simple direct search method similar to direct binary search method for binary holograms generation. Main difference is that proposed direct search with random trajectory method designed to process arrays with multiple phase levels. First, kinoform is generated with conventional method such as Gerchberg-Saxton. Then, elements of kinoform are sequentially switched to obtain lower normalized standard deviation (NSTD) of reconstructed image from desired image. This process goes on until minimum NSTD drop level is reached. Proposed method provides average NSTD decrease 26%.

We present three-dimensional photon counting microscopy using Bayesian estimation. To record the light intensity information of objects in photon-starved conditions, photon counting imaging can be used. In conventional photon counting imaging, maximum likelihood estimation (MLE) or Bayesian estimation with uniform statistical parameters has been used for 3D visualization. Since MLE does not use the prior information of the estimated target, its visual quality is not enough to recognize 3D microorganisms when low number of photons is used. In addition, because Bayesian estimation with uniform statistical parameters uses fixed statistical parameters over the whole image, the estimated image seems to be image with boost-up light intensity. On the other hand, our proposed method uses the nonuniform statistical parameters for prior information of microorganisms to estimate 3D profile of them. Therefore, this method may enhance the visual quality of 3D microscopy results with low number of photons.

This research is conducted in order to design a spectral device for light sources power spectrum analysis. The spectral device should process radiation from sources, direct contact with radiation of which is either impossible or undesirable. Such sources include jet blast of an aircraft, optical radiation in metallurgy and textile industry. In proposed spectral device optical radiation is guided out of unfavorable environment via a piece of optical fiber with high dispersion. It is necessary for analysis to make samples of analyzed radiation as short pulses. Dispersion properties of such optical fiber cause spectral decomposition of input optical pulses. The faster time of group delay vary the stronger the spectral decomposition effect. This effect allows using optical fiber with high dispersion as a major element of proposed spectral device. Duration of sample must be much shorter than group delay time difference of a dispersive system. In the given frequency range this characteristic has to be linear. The frequency range is 400 … 500 THz for typical optical fiber. Using photonic-crystal fiber (PCF) gives much wider spectral range for analysis. In this paper we propose simulation of single pulse transmission through dispersive system with linear dispersion characteristic and quadratic-detected output responses accumulation. During simulation we propose studying influence of optical fiber dispersion characteristic angle on spectral measurement results. We also consider pulse duration and group delay time difference impact on output pulse shape and duration. Results show the most suitable dispersion characteristic that allow choosing the structure of PCF – major element of time-dispersion spectral analysis method and required number of samples for reliable assessment of measured spectrum.

With the camera internal parameters known, to calculate the external parameters is to solve a set of highly nonlinear over-determined equations. In this paper, an improved hybrid genetic algorithm is adopted to obtain external parameters. It combines the advantages of genetic algorithm and Newton method, making it possible to obtain results with high accuracy and a faster convergence.

The broadband passive optical network (BPON) has the ability to support high-speed data, voice, and video services to home and small businesses customers. In this work, the performance of bi-directional BPON is analyzed for both down and up streams traffic cases by the help of erbium doped fiber amplifier (EDFA). The importance of BPON is reduced cost. Because PBON uses a splitter the cost of the maintenance between the providers and the customers side is suitable. In the proposed research, BPON has been tested by the use of bit error rate (BER) analyzer. BER analyzer realizes maximum Q factor, minimum bit error rate, and eye height.

The Advance Radiographic Capability (ARC) at the National Ignition Facility (NIF) is a laser system that employs up to four petawatt (PW) lasers to produce a sequence of short pulses that generate X-rays which backlight highdensity internal confinement fusion (ICF) targets. Employing up to eight backlighters, ARC can produce an X-ray "motion picture" to diagnose the compression and ignition of a cryogenic deuterium-tritium target with tens-ofpicosecond temporal resolution during the critical phases of an ICF shot. Multi-frame, hard-X-ray radiography of imploding NIF capsules is a capability which is critical to the success of NIF's missions. The function of the Centering and Pointing System (CAPS) in ARC is to provide superimposed near-field and far-field images on a common optical path. The Images are then analyzed to extract beam centering and pointing data for the control system. The images contain the confluence of pointing, centering, and reference patterns. The patterns may have uneven illumination, particularly when the laser is misaligned. In addition, the simultaneous appearance of three reference patterns may be co-incidental, possibly masking one or more of the patterns. Image analysis algorithms have been developed to determine the centering and pointing position of ARC from these images. In the paper we describe the image analysis algorithms used to detect and identify the centers of these patterns. Results are provided, illustrating how well the process meets system requirements.

This paper presents a parallel algorithm designed for 1/f noise signal estimation based on Compressed sensing theory on the GPU platform. In the accelerating process, we select parts of the serial program as the object to be speeded up for the execution time of algorithm. Compared with the conventional methods for 1/f noise estimation, our scheme has shown a 20x speedup.

In this paper, we aimed to separate the 1/f noise from the original signal, and analyzed its characteristics of power spectrum. First, an N-level wavelet transform has been applied to the original data signal before the compressed sensing observation for the original signal. Compared with the tradition measurement procession of compressed sensing, the measurement matrix here is replaced with the circulant matrix. This can greatly reduce the measurement number compared with the random Gaussian matrix. To reduce the algorithm time, some zero independent elements are introduced to the circulant matrix. This proposed circulant matrix is then helpful to save 60 percent of algorithm’s reconstruction time.