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In this paper, we present an industrial application of multispectral imaging, for density measurement of colorants in photographic paper. We designed and developed a 9-band LED illumination based multispectral imaging system specifically for this application in collaboration with FUJIFILM Manufacturing Europe B.V., Tilburg, Netherlands. Unlike a densitometer, which is a spot density measurement device, the proposed system enables fast density measurement in a large area of a photo paper. Densities of the four colorants (CMYK) at every surface point in an image are calculated from the spectral reflectance image. Fast density measurements facilitate automatic monitoring of density changes (which is proportional to thickness changes), which helps control the manufacturing process for quality and consistent output. Experimental results confirm the effectiveness of the proposed system.

There are several paradigms for color generation in reflective displays (e-Paper) including RGBW color filtering or stacked RGB or CMY. Theoretically, the highest white state reflectance and best color gamut are achieved by stacking three layers of pixels. However, stacking 3 layers induces significant optical losses especially at high resolution and typically does not allow for video operation. Therefore RGBW color filtering is currently preferred for higher resolution and single-layer e-Paper, but only provides color at 25% of the area and a maximum theoretical white reflectance of 50%. Presented herein is a new bi-primary color-system that cooperatively displays two complimentary colors inside a single sub-pixel, and therefore doubles the white state reflectance and color gamut for single-layer e-Paper. Also discussed are candidate e-Paper technologies that may be able to adopt the bi-primary color system, including possible advantages and challenges for each technology.

We describe a two-layer neural network using holographic optical disks as the interconnection weights. Such a system can be used to implement one two-layer with a large number of hidden units, or several two-layer networks with a smaller number of hidden units© (1992) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Rotation-invariant pattern recognition is shown to have intrinsic limitations determined by the set of patterns to be recognized and by the specific optical setup. Within these limitations, a general procedure is proposed for the generation of bipolar filters that do not require the sensitive alignment procedures involved in holographic filters and are suitable for superposition synthesis to achieve rotation invariance.

Due to challenges in the visual interpretation of radar signatures or in the subsequent information extraction, a fusion with other data sources can be beneficial. The most accurate basis for a fusion of any kind of remote sensing data is the mapping of the acquired 2D image space onto the true 3D geometry of the scenery. In the case of radar images this is a challenging task because the coordinate system is based on the measured range which causes ambiguous regions due to layover effects. This paper describes a method that accurately maps the detailed 3D information of a scene to the slant-range-based coordinate system of an imaging radar. Due to this mapping all the contributing geometrical parts of one resolution cell can be determined in 3D space. The proposed method is highly efficient, because computationally expensive operations can be directly performed on graphics card hardware. The described approach builds a perfect basis for sophisticated methods to extract data from multiple complimentary sensors like from radar and optical images, especially because true 3D information from whole cities will be available in the near future. The performance of the developed methods will be demonstrated with high resolution radar data acquired by the space borne SAR-sensor TerraSAR-X. The most accurate basis for a fusion of any kind of remote sensing data is the mapping of the acquired 2D image space onto the true 3D geometry of the scenery. In the case of radar images this is a challenging task because the coordinate system is based on the measured range which causes ambiguous regions due to layover effects. This paper describes a method that accurately maps the detailed 3D information of a scene to the slant-range-based coordinate system of an imaging radar. The performance of the developed methods will be demonstrated with high resolution radar data acquired by the space borne SAR-sensor TerraSAR-X.

The article of record as published may be found at http://dx.doi.org/10.1117/12.2263096 This paper examines the implications pertaining to the problem of attempting to invert synthetic aperture radar (SAR) measurement data to yield unique estimates of the underlying motion of slow targets in the imaged scene. A recent analysis has demonstrated that ambiguities exist in estimating the kinematics parameters of surface targets for general bistatic SAR collection data. In particular, a procedure has been developed which generates alternate target trajectories which give the same SAR measurements as that of the true target motion. The current paper extends the earlier analysis by generating specific numeric examples of alternate target trajectories corresponding to the motion of a given slowly moving target. This slow-target case reveals the counter-intuitive result that a single SAR collection data set can be generated by target trajectories with significantly different, and possibly opposing, heading directions. For example, the true motion of a given target can be moving towards the mean radar position during the SAR collection interval, whereas a valid alternate trajectory can correspond to a target that is moving away from the radar. The present analysis demonstrates the extent of the challenges associated with attempting to estimate of the underlying motion of targets using SAR measurement data. AFRL for partial sponsorship

In this paper, we investigate quality factors of numerical reconstruction with a small number of signals based on sparsity from a holographic fringe pattern. Holographic fringe pattern generated by Fresnel diffraction is a complex amplitude and sparse distribution in frequency domain. The sparsity of holographic fringe pattern could play a key role in reconstruction quality assessment in compressive holography. In this paper we have investigated sparsity constraint on holographic fringe pattern which influences the overall quality of numerically reconstructed data. In addition, we have investigated reconstruction quality for various subsampling methods including uniform sampling, random sampling, variable density sampling, and magnitude-based sampling. Experiments have been conducted to evaluate reconstruction qualities on sparsity constraints and sampling patterns. Experimental results indicate that the way to extract the sparse signals could significantly affect the quality of the numerical reconstruction in digital holography and visually plausible reconstruction could be obtained with a sparse holographic fringe pattern.

Today’s CD-SEM metrology is challenged when it comes to measuring complex features found in patterning hotspots (like tip to tip, tip to side, necking and bridging). Metrology analysis tools allow us to extract SEM contours of a feature and convert them into a GDS format from which dimensional data can be extracted. While the CD-SEM is being used to take images, the actual measurement and the choice of what needs to be measured is done offline. Most of the time this method is used for OPC model creation but barely for process variability analysis at nominal process conditions. We showed in a previous paper [1] that it is possible to study lithography to etch transfer behavior of a hotspot using SEM contours. The goal of the current paper is to go extend this methodology to quantify process variability of 2D features using a new tooling to measure contour data.

This paper presents our research findings on high-speed 3D imaging using digital light processing (DLP) technologies. In particular, we compare two different sinusoidal fringe generation techniques using the DLP projection devices: direct projection of 8-bit computer generated sinusoidal patterns (a.k.a, the sinusoidal method), and the creation of sinusoidal patterns by defocusing binary patterns (a.k.a., the binary defocusing method). This paper mainly examines their performance on high-accuracy measurement applications under precisely controlled settings. Two different projection systems were tested in this study: the commercially available inexpensive projector, and the DLP development kit. Experimental results demonstrated that the binary defocusing method always outperforms the sinusoidal method if a sufficient number of phase-shifted fringe patterns can be used.

Security is one of the big issues in automated teller machine (ATM). In ATM, two types of security have to be maintained. One is to secure displayed information. The other is to secure screen contamination. This paper gives a solution for these two security issues. In order to secure information against peeping at the screen, we utilize visual cryptography for displayed information and limit the viewing zone. Furthermore, an aerial information screen with aerial imaging by retro-reflection, named AIRR enables users to avoid direct touch on the information screen. The purpose of this paper is to propose an aerial secure display technique that ensures security of displayed information as well as security against contamination problem on screen touch. We have developed a polarization-processing display that is composed of a backlight, a polarizer, a background LCD panel, a gap, a half-wave retarder, and a foreground LCD panel. Polarization angle is rotated with the LCD panels. We have constructed a polarization encryption code set. Size of displayed images are designed to limit the viewing position. Furthermore, this polarization-processing display has been introduced into our aerial imaging optics, which employs a reflective polarizer and a retro-reflector covered with a quarter-wave retarder. Polarization-modulated light forms the real image over the reflective polarizer. We have successfully formed aerial information screen that shows the secret image with a limited viewing position. This is the first realization of aerial secure display by use of polarization-processing display with retarder-film and retro-reflector.

Because of go-stop mode not applying to FMCW CSAR (frequency modulated continuous wave circular synthetic aperture radar), received signal include Doppler shifting result from the radar fly in one period, which have a bad effect on the quality of imaging in wide-field FMCW CSAR. However the compensation functions of liner SAR are not suitable for CSAR. To solve the problem, the paper rebuild a received mode and elicit the Doppler shifting. At the same time, based on the model, the paper analysis the layover phenomenon while obtaining two-dimensional (2D) representations of 3D large scenes due to the wide-field FMCW CSAR and simulate the phenomenon. By the simulation, the effect of the layover can be expressed clearly.

The Visible Broadband Imager (VBI) Blue and Red channels are the first Daniel K. Inouye Solar Telescope (DKIST) instruments that have been aligned and tested in a laboratory. This paper describes the optical alignment method of the VBI as performed in the laboratory. The objective of this preliminary alignment is to test and validate the optical alignment method that will be used during final alignment on the telescope, to measure the VBI performances and to verify that it meets specification. The optical alignment method is defined by three major steps. The first step is realized by combining the optical and mechanical models into the Spatial Analyzer (SA) software, and extracting the data serving as target values during alignment. The second step is the mechanical alignment and allows to accurately position the optics in the instrument coordinate system by using a Coordinate Measurement Machine (CMM) arm and a theodolite. This step has led to a great initial positioning and has allowed reaching an initial wavefront error before optical alignment close to the specification. The last step, performed by interferometry, allows fine alignment to compensate the residual aberrations created by misalignment and manufacturing tolerances. This paper presents also an alignment method to compute the shifts and tilts of compensating lenses to correct the residual aberrations. This paper describes first results of the VBI instruments performances measured in the laboratory and confirm the validity of the alignment process that will be reproduced during final alignment on the telescope.

Surfaces with specular, non-Lambertian reflectance are common in urban areas. Robot perception systems for applications in urban environments need to function effectively in the presence of such materials; however, both passive and active 3-D perception systems have difficulties with them. In this paper, we develop an approach using a stereo pair of polarization cameras to improve passive 3-D perception of specular surfaces. We use a commercial stereo camera pair with rotatable polarization filters in front of each lens to capture images with multiple orientations of the polarization filter. From these images, we estimate the degree of linear polarization (DOLP) and the angle of polarization (AOP) at each pixel in at least one camera. The AOP constrains the corresponding surface normal in the scene to lie in the plane of the observed angle of polarization. We embody this constraint an energy functional for a regularization-based stereo vision algorithm. This paper describes the theory of polarization needed for this approach, describes the new stereo vision algorithm, and presents results on synthetic and real images to evaluate performance.

Radar target identification using probabilistic vector machines is investigated and tested using real radar data collected in a compact range for commercial aircraft models. Unlike relevance vector machines (RVM) that utilize zero-mean Gaussian prior for every weight for both negative and positive classes and are thus vulnerable to questionable (deceptive) vectors, probabilistic vector machines [2], alternatively, use nonnegative priors for the positive class and vice versa. This paper compares the performance of these machines with other target identification tools, and highlights scenarios where classification via a probabilistic vector machine is more plausible. The problem addressed in this paper is a M-ary target classification problem and is implemented as a set of pairwise comparisons between all competing hypotheses.

This paper proposes a new zoom lens design with intermediate image. The concept of intermediate optics is applied in this paper in order to minimize size of front diameter. The final layout shows the proposed 9x zoom lens can effectively miniature the front diameter of lens about 44.25%.

The main purpose of this paper is to introduce a high speed zoom lens for photography. The lens operates with a full field angle that encompasses more than 86 degrees and the corner illumination is more than 60 percent at the wide end. In addition, the paper provides guidance on how to effectively use an aspheric surface in the first lens group consisting of an NPNPP (negative, positive, negative, positive, and positive). This treatment includes distortion considerations. Useful design solutions using an aspheric surface are introduced along with assessment of the resulting designs. Finally, a strategy to correct field curvature in this zoom lens is shown with an example.

The paper is understood as a continuation of a series of papers on surface metrology for application in quality control of printed matter. A stereoscopic device for extremely rugged applications, especially in quality control in printing industry, is presented. The device developed is based on variable tilted delay elements, which allow the use of a single imaging sensor and robust definition of parallax shift. Variable orthogonal delay elements were already used for variation of plane of focus in surface inspection, as described in previous papers. The method can be applied for macroscopical as well as for microscopic imaging. Beside mechanical design issues, the theoretical description, geometrical-optical approaches, and the treatment of the dispersion problem are discussed. Experimental results are included.

This paper describes the impact of ground mover motion and windowing on stationary and moving shadows in Synthetic Aperture Radar (SAR) and video SAR mode imagery. The technique provides a foundation for optimizing algorithms that detect ground movers in SAR imagery. The video SAR mode provides a persistent view of a scene centered at the Motion Compensation Point (MCP). The radar platform follows a circular flight path. Detecting a stationary shadow in a SAR image is important because the shadow indicates a detection of an object with a height component near the shadow. Similarly, the detection of a shadow that moves from frame to frame indicates the detection of a ground mover at the location of the moving shadow. An approach analyzes the impact of windowing in calculating the brightness of a pixel in a stationary, finite-sized shadow region. An extension of the approach describes the pixel brightness for a moving shadow as a function of its velocity. The pixel brightness provides an upper bound on the Probability of Detection (PD) and a lower bound on the Probability of False Alarm (PFA) for a finite-sized, stationary or moving shadow in the presence of homogeneous, ideal clutter. Synthetic data provides shadow characteristics for a radar scenario that lend themselves for detecting a ground mover. The paper presents 2011-2014 flight data collected by General Atomics Aeronautical Systems, Inc. (GA-ASI).

Integrate circuit (IC) technology is going through multiple changes in terms of patterning techniques (multiple patterning, EUV and DSA), device architectures (FinFET, nanowire, graphene) and patterning scale (few nanometers). These changes require tight controls on processes and measurements to achieve the required device performance, and challenge the metrology and process control in terms of capability and quality. Multivariate data with complex nonlinear trends and correlations generally cannot be described well by mathematical or parametric models but can be relatively easily learned by computing machines and used to predict or extrapolate. This paper introduces the predictive metrology approach which has been applied to three different applications. Machine learning and predictive analytics have been leveraged to accurately predict dimensions of EUV resist patterns down to 18 nm half pitch leveraging resist shrinkage patterns. These patterns could not be directly and accurately measured due to metrology tool limitations. Machine learning has also been applied to predict the electrical performance early in the process pipeline for deep trench capacitance and metal line resistance. As the wafer goes through various processes its associated cost multiplies. It may take days to weeks to get the electrical performance readout. Predicting the electrical performance early on can be very valuable in enabling timely actionable decision such as rework, scrap, feedforward, feedback predicted information or information derived from prediction to improve or monitor processes. This paper provides a general overview of machine learning and advanced analytics application in the advanced semiconductor development and manufacturing.

In this paper, we investigate two error issues in stereo images, which may produce visual fatigue. When two cameras are used to produce 3D video sequences, vertical misalignment can be a problem. Although this problem may not occur in professionally produced 3D programs, it is still a major issue in many low-cost 3D programs. Recently, efforts have been made to produce 3D video programs using smart phones or tablets, which may present the vertical alignment problem. Also, in 2D-3D conversion techniques, the simulated frame may have blur effects, which can also introduce visual fatigue in 3D programs. In this paper, to investigate the relationship between these two errors (vertical misalignment and blurring in one image), we performed a subjective test using simulated 3D video sequences that include stereo video sequences with various vertical misalignments and blurring in a stereo image. We present some analyses along with objective models to predict the degree of visual fatigue from vertical misalignment and blurring.

Infrared character of aircraft is one important factor to estimate the ability of breaching the defense of enemy, this paper firstly analyzed the method of infrared calibration with collimator and energy factors composing the sky background, propose one method of deleting energy of background within current image; furthermore, the paper points out that the parameters of calibration with collimator can’t be directly applied to computing Infrared character of flying target, and based on that propose the method of deleting energy of background with another background image measured before mission.

In this study, this paper focus on the vision-based autonomous helicopter unmanned aerial vehicle (UAV) landing problems. This paper proposed a multisensory fusion to autonomous landing of an UAV. The systems include an infrared camera, an Ultra-wideband radar that measure distance between UAV and Ground-Based system, an PAN-Tilt Unit (PTU). In order to identify all weather UAV targets, we use infrared cameras. To reduce the complexity of the stereovision or one-cameral calculating the target of three-dimensional coordinates, using the ultra-wideband radar distance module provides visual depth information, real-time Image-PTU tracking UAV and calculate the UAV threedimensional coordinates. Compared to the DGPS, the test results show that the paper is effectiveness and robustness.

This paper presents the development of methods for real-time fine-tuning of a high power laser welding process of thick steel by using a compact smart camera system. When performing welding in butt-joint configuration, the laser beam’s location needs to be adjusted exactly according to the seam line in order to allow the injected energy to be absorbed uniformly into both steel sheets. In this paper, on-line extraction of seam parameters is targeted by taking advantage of a combination of dynamic image intensity compression, image segmentation with a focal-plane processor ASIC, and Hough transform on an associated FPGA. Additional filtering of Hough line candidates based on temporal windowing is further applied to reduce unrealistic frame-to-frame tracking variations. The proposed methods are implemented in Matlab by using image data captured with adaptive integration time. The simulations are performed in a hardware oriented way to allow real-time implementation of the algorithms on the smart camera system.

In this paper a method to detect the electrical circuit elements from the scanned images of electrical drawings is proposed. The method, based on histogram analysis and mathematical morphology, detects the circuit elements, for example, circuit components, wires, and generates a connectivity matrix which may be used to find similar, but spatially different looking circuit using graph isomorphism. The work may also be used for vectorization of the circuit drawings utilising the information on the segmented circuit elements and corresponding connectivity matrix. The novelty of the method lies in its simplicity and adaptability to work with a tolerable skewed image and the capability to segment symbols irrespective of their orientation. The proposed method is tested over a data-set containing more than one hundred scanned images of a variety of electrical drawings. Some of the results are presented in this paper to show the efficacy and robustness of the proposed method.

Spherical stereo vision is a kind of stereo vision system built by fish-eye lenses, which discussing the stereo algorithms conform to the spherical model. Epipolar geometry is the theory which describes the relationship of the two imaging plane in cameras for the stereo vision system based on perspective projection model. However, the epipolar in uncorrected fish-eye image will not be a line but an arc which intersects at the poles. It is polar curve. In this paper, the theory of nonlinear epipolar geometry will be explored and the method of nonlinear epipolar rectification will be proposed to eliminate the vertical parallax between two fish-eye images. Maximally Stable Extremal Region (MSER) utilizes grayscale as independent variables, and uses the local extremum of the area variation as the testing results. It is demonstrated in literatures that MSER is only depending on the gray variations of images, and not relating with local structural characteristics and resolution of image. Here, MSER will be combined with the nonlinear epipolar rectification method proposed in this paper. The intersection of the rectified epipolar and the corresponding MSER region is determined as the feature set of spherical stereo vision. Experiments show that this study achieved the expected results.

Coded structure light is widely used for 3D scanning, and different coding strategies are adopted to suit for different goals. In this paper, three coding strategies are compared, and one of them is selected to implement a low cost structure light scanner under the cost of €100. To reach this goal, the projector and the video camera must be the cheapest, which will lead to some problems related to light coding. For a cheapest projector, complex intensity pattern can’t be generated; even if it can be generated, it can’t be captured by a cheapest camera. Based on Gray code, three different strategies are implemented and compared, called phase-shift, line-shift, and bit-shift, respectively. The bit-shift Gray code is the contribution of this paper, in which a simple, stable light pattern is used to generate dense(mean points distance

Lane detection and tracking play important roles in lane departure warning system (LDWS). In order to improve the real-time performance and obtain better lane detection results, an improved algorithm of lane detection and tracking based on combination of improved Hough transform and least-squares fitting method is proposed in this paper. In the image pre-processing stage, firstly a multi-gradient Sobel operator is used to obtain the edge map of road images, secondly adaptive Otsu algorithm is used to obtain binary image, and in order to meet the precision requirements of single pixel, fast parallel thinning algorithm is used to get the skeleton map of binary image. And then, lane lines are initially detected by using polar angle constraint Hough transform, which has narrowed the scope of searching. At last, during the tracking phase, based on the detection result of the previous image frame, a dynamic region of interest (ROI) is set up, and within the predicted dynamic ROI, least-squares fitting method is used to fit the lane line, which has greatly reduced the algorithm calculation. And also a failure judgment module is added in this paper to improve the detection reliability. When the least-squares fitting method is failed, the polar angle constraint Hough transform is restarted for initial detection, which has achieved a coordination of Hough transform and least-squares fitting method. The algorithm in this paper takes into account the robustness of Hough transform and the real-time performance of least-squares fitting method, and sets up a dynamic ROI for lane detection. Experimental results show that it has a good performance of lane recognition, and the average time to complete the preprocessing and lane recognition of one road map is less than 25ms, which has proved that the algorithm has good real-time performance and strong robustness.

A phase-only hologram (POH) has two major advantages. First, it can be displayed with a single phase-only SLM. Second, the reconstructed image is brighter, and free from the zeroth-order diffraction and the twin image. In this paper, four modern methods for the generation of POH, are reviewed. Being different from some existing approach that involved multiple epochs of evaluation in the generation of POH, the methods describe in this paper are non-iterative and computationally efficient. Moreover, these works also share the common feature that the holograms generated can be displayed directly on the phase-only SLM, hence simplifying the optical setup.

In order to develop a high accuracy optical alignment system for precision molding machine, a geometric matching method was developed in this paper. The alignment system includes 4 high magnification lenses, 4 CCD cameras and 4 LED light sources. In the precision molding machine, a bottom metal mold and a top glass mold are used to produce a micro lens. The two molds combination does not use any pin or alignment part. They only use the optical alignment system to alignment. In this optical alignment system, the off-axis alignment method was used. The alignment accuracy of the alignment system is about 0.5 μm. There are 2 cross marks on the top glass mold and 2 cross marks on the bottom metal mod. In this paper did not use edge detection to recognize the mask center because the mask easy wears when the combination times increased. Therefore, this paper develops a geometric matching method to recognize mask center.

In this paper, we present a novel optical design to overcome the over-exposure problem without increasing the specifications of sensors. A spatial light modulator (SLM), which is commonly used for modulating light intensity, is used in our design. In projector systems, SLM is commonly used in conjunction with DMD to modulate the intensity of the projected images. In our design, reverse of this design concept is employed. Intensity modulation is performed on object space, instead of image space. This paper shows two optical designs, one is image system, which image the outside object to SLM. This system has F/8 and Field of View (FOV) 40 degree Hyperfocal image design. The other is a relay image system, which relay the image from SLM to sensor. This relay system has F/4 and magnification of 0.5 times. Our design has successfully reduced over-exposure problems.

This paper deals with new optical non-conventional 3D laser imaging. Optical non-conventional imaging explores the advantages of laser imaging to form a three-dimensional image of the scene. 3D laser imaging can be used for threedimensional medical imaging, topography, surveillance, robotic vision because of ability to detect and recognize objects. In this paper, we present a 3D laser imaging for concealed object identification. The objective of this new 3D laser imaging is to provide the user a complete 3D reconstruction of the concealed object from available 2D data limited in number and with low representativeness. The 2D laser data used in this paper come from simulations that are based on the calculation of the laser interactions with the different interfaces of the scene of interest and from experimental results. We show the global 3D reconstruction procedures capable to separate objects from foliage and reconstruct a threedimensional image of the considered object. In this paper, we present examples of reconstruction and completion of three-dimensional images and we analyse the different parameters of the identification process such as resolution, the scenario of camouflage, noise impact and lacunarity degree.

This paper describes a correction technique using stereo SAR (Synthetic Aperture Radar) that improves the image quality of video SAR. The video SAR mode provides a persistent view of a scene centered at the Motion Compensation Point (MCP). The radar platform follows a circular flight path. The effect of height-dependent layover in video SAR imagery is that objects higher than the image plane appear translated towards the along-track direction in the image plane. A Digital Elevation Map (DEM) provides the height of the MCP. A height error in the MCP results in a SAR image that is not centered at the MCP. An objective is to form a sequence of SAR images centering the MCP for each image. This paper details a correlation method performed on a pair of SAR images in order to estimate the layover. Using multiple pairs of images taken from video SAR imagery improves the reliability of the layover estimate. Synthetic target imagery with targets at non-zero heights demonstrates the method. The paper presents 2011-2013 flight data collected by General Atomics Aeronautical Systems, Inc. (GA-ASI) implementing the video SAR mode with correction for layover. The flight data demonstrates good video quality with the MCP centered in each video frame.

We present a novel approach to use mountain drainage patterns for GPS-Denied navigation of small unmanned aerial systems (UAS) such as the ScanEagle, utilizing a down-looking fixed focus monocular imager. Our proposal allows extension of missions to GPS-denied mountain areas, with no assumption of human-made geographic objects. We leverage the analogy between mountain drainage patterns, human arteriograms, and human fingerprints, to match local drainage patterns to Graphics Processing Unit (GPU) rendered parallax occlusion maps of geo-registered radar returns (GRRR). Details of our actual GPU algorithm is beyond the subject of this paper, and is planned as a future paper. The matching occurs in real-time, while GRRR data is loaded on-board the aircraft pre-mission, so as not to require a scanning aperture radar during the mission. For recognition purposes, we represent a given mountain area with a set of spatially distributed mountain minutiae, i.e., details found in the drainage patterns, so that conventional minutiae-based fingerprint matching approaches can be used to match real-time camera image against template images in the training set. We use medical arteriography processing techniques to extract the patterns. The minutiae-based representation of mountains is achieved by first exposing mountain ridges and valleys with a series of filters and then extracting mountain minutiae from these ridges/valleys. Our results are experimentally validated on actual terrain data and show the effectiveness of minutiae-based mountain representation method. Furthermore, we study how to select landmarks for UAS navigation based on the proposed mountain representation and give a set of examples to show its feasibility. This research was in part funded by Rockwell Collins Inc.

In order to get measures with a high accurate, three-dimensional reconstruction systems are implemented in industrial, medical, and investigative fields. To obtain high accurate is necessary to carry out an appropriate calibration procedure. In fringe projection profilometry, this procedure allows obtaining a relation between absolute phase and three-dimensional (3D) information of the object in study; however, to execute such procedure a precise movement stage is required. A fringe projection system is formed by a projector, a digital camera and a control unit, called like a projection-acquisition unit in this paper. The calibration of the projection-acquisition unit consists in to establish the parameters that are required to transform the phase of the projected fringes to metric coordinates of the object surface. These parameters are a function of the intrinsic and extrinsic parameters of both camera and projector, due to the projector is modeled as an inverse camera. For this purpose, in this paper a novel and flexible calibration method that allows calibrating any device that works with fringe projection profilometry is proposed. In this method is used a reference plane placed in random positions and the projection of an encoded pattern of control points. The camera parameters are computed using Zhang’s calibration method; and the projector parameters are computed from the camera parameters and the phase of the pattern of control points, which is determined by using Fourier analysis. Experimental results are presented to demonstrate the performance of the calibration method.

In this paper, we present a novel and clinically valuable software platform for automatic ulcer detection on gastrointestinal (GI) tract from Capsule Endoscopy (CE) videos. Typical CE videos take about 8 hours. They have to be reviewed manually by physicians to detect and locate diseases such as ulcers and bleedings. The process is time consuming. Moreover, because of the long-time manual review, it is easy to lead to miss-finding. Working with our collaborators, we were focusing on developing a software platform called GISentinel, which can fully automated GI tract ulcer detection and classification. This software includes 3 parts: the frequency based Log-Gabor filter regions of interest (ROI) extraction, the unique feature selection and validation method (e.g. illumination invariant feature, color independent features, and symmetrical texture features), and the cascade SVM classification for handling "ulcer vs. non-ulcer" cases. After the experiments, this SW gave descent results. In frame-wise, the ulcer detection rate is 69.65% (319/458). In instance-wise, the ulcer detection rate is 82.35%(28/34).The false alarm rate is 16.43% (34/207). This work is a part of our innovative 2D/3D based GI tract disease detection software platform. The final goal of this SW is to find and classification of major GI tract diseases intelligently, such as bleeding, ulcer, and polyp from the CE videos. This paper will mainly describe the automatic ulcer detection functional module.

A structured-light system for depth estimation is a type of 3D active sensor that consists of a structured-light projector that projects an illumination pattern on the scene (e.g. mask with vertical stripes) and a camera which captures the illuminated scene. Based on the received patterns, depths of different regions in the scene can be inferred. In this paper, we use side information in the form of image structure to enhance the depth map. This side information is obtained from the received light pattern image reflected by the scene itself. The processing steps run real time. This post-processing stage in the form of depth map enhancement can be used for better hand gesture recognition, as is illustrated in this paper.

Although High Dynamic Range (HDR) imaging has represented, in the recent years, the topic of important researches, it has not reached yet an excellent level of the HDR scenes ac quisition using the available co mponents. Indeed, many solu-tions have been proposed ranging from bracketing to the beamsp litter but none of these solutions is really consistent with the moving scenes representing light’s level difference. In this paper, we present an optical architecture, which exploits the stereoscopic cameras, ensuring the simultaneous capture of four different ex posures of the same image on four sensors with efficient use of the available light. We also present a short description of the implemented fusion algorithm implemented. Keywords : Stereoscopic cameras, beamsplitters, APEX , HDR Imaging, Cameras architecture, AMP 1. Introduction The extensive development of computer tools is in effervescen ce year by year. It remains on e of the emerging techniques introduced in numerous applications such as quality control, medicine, and video surveillance. The artificial vision tech-niques are adapted to the envisaged applica tions and to the associated constraints. Along with this, the researches in the field of HDR images’ are constantly evolving. Indeed, the process of capturing HDR images has been the work subject of many researchers and hundreds of artists and photographers. As a result, there are many articles and patents describing methods and systems for capturing HDR images. The easiest way to HDR imag-ing involves taking a series of pictures with different exposure times [1, 2]. A lthough this method works well for static scenes, it is unfortunately not well suited for video because of different exposure times for each image, which result in varying amounts of motion blur and other effects occurring after the time of use. However, researchers have extended this approach to video capturing with alternating bright and dark exhibitions [3, 4]. In our case, we will use the stereoscopic technology to generate High Dynamic Range (HDR) images. In order to achieve that, we require three to five images with different exposures. With the combination between two lenses of a camera and a beam splitter, we can get up to four differen t images. Thus, we will study the necessary diaphragm opening allowing us to get the best exposures and define the architecture that we would deploy. The paper will be organized as follow. In the section II, we will discuss about the researches related to stereoscopic cameras and HDR images. Then, Section III will detail the proposed architectur e, the criteria to be met and the results that are expected to get. Finally, th is article will finish by a conclusion and an introduction of some perspectives.

In this keynote address paper, we present an overview of our previously published work on using compressive sensing in multi-dimensional imaging. We shall examine a variety of multi dimensional imaging approaches and applications, including 3D multi modal imaging integrated with polarimetric and multi spectral imaging, integral imaging and digital holography. This Keynote Address paper is an overview of our previously reported work on 3D imaging with compressive sensing.

Publisher’s Note: This paper, originally published on 9/26/2013, was replaced with a corrected/revised version on 7/9/2014. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. Significant research efforts have been invested in attempting to reliably capture and visualize holograms since their inception in 1962. However, less attention has been given to the efficient digital representation of the recorded holograms, which differ considerably from digitally recorded photographs. This paper examines the properties of recorded off-axis holograms and attempts to find a suitable sparse representation for holographic data. Results show significantly improved Bjontegaard delta PSNR of over 4.5 dB on average within a bit-rate range of 0.125 to 2 bpp when combining the direction-adaptive discrete wavelet transform with non-standard decomposition schemes for off-axis holographic recordings; up to 7.5% reduction of file size has been achieved in the lossless case.

Glaucoma was diagnosed or tracked by the intraocular pressure (IOP) generally because it is one of the physiology parameters that are associated with glaucoma. But measurement of IOP is not easy and consistence under different measure conditions. An infrared videopupillography is apparatus to monitor the pupil size in an attempt to bypass the direct IOP measurement. This paper propose an infrared videopupillography to monitoring the pupil size of different light stimulus in dark room. The portable infrared videopupillography contains a camera, a beam splitter, the visible-light LEDs for stimulating the eyes, and the infrared LEDs for lighting the eyes. It is lighter and smaller than the present product. It can modulate for different locations of different eyes, and can be mounted on any eyeglass frame. An analysis program of pupil size can evaluate the pupil diameter by image correlation. In our experiments, the eye diameter curves were not smooth and jagged. It caused by the light spots, lone eyelashes, and blink. In the future, we will improve the analysis program of pupil size and seek the approach to solve the LED light spots. And we hope this infrared videopupillography proposed in this paper can be a measuring platform to explore the relations between the different diseases and pupil response.

On the basis of the principle of polarization detection, a hyper-spectral polarization imaging system, which is based on linear polarizer and acousto-optic tunable filter (AOTF), was designed to detect and recognize camouflage target intelligently and rapidly in this paper. Our design has neither moving parts nor modulation, and has fast and electronically tuning property, so a quick scan of spectrum at 400 nm~1000 nm can be realized electronically. At the same time, it not only could obtain the intensity image, hyper-spectral information, but also could acquire polarization signatures of the scene. Then the spectral polarization experiment about aluminous plane which covered with the bottle green, shallow green and khaki camouflage pigments within meadow were conducted at specifically wavelength by the instrument. Finally, the polarization information of the man-made targets and natural background in the scene, and the fusion image based on HIS color space were deduced through processing the experiment data. The experimental result demonstrates that the polarization characteristics of camouflage pigments were different from that of natural background. As the contrast of target and background could be enhanced by polarization information, the camouflage target could be identified effectively from the image according to polarization information. On the other hand, the camouflage target is more obvious in the fused image. Therefore, the proposed method and the system in this paper are reasonable and effective. Consequently, the hyper-spectral polarization detection technique which relative to the classical intensity detection is of significance to improve the accuracy of recognition of camouflage targets in mixed background under proper detection condition.

In order to establish measurement basis in non-cooperative environment, this paper proposes an autonomous position and posture servo tracking method based on laser light guided monocular vision. The light of a linear laser projected on a plane was simulated as horizon basis, while the laser light modulated by the projection in the reference plane was taken as servo target. The modulated position and posture change information of laser light was obtained by monocular vision system, information from which the attitude angle of the laser light could be calculated. The attitude angle was transmitted to parallel tracking platform in real time and controlled the movement of the platform according to the laser light. The tracking angle parameters of parallel tracking platform under different position and posture were verified using an inclinometer, which proved the validity and effectiveness of this method. As to the existing measurement errors, this paper analyzed possible causes and provided with feasible suggestions to further improve the precision of the system.

Many technologies are being developed to improve the detection of buried threats (e.g., landmines) and to discriminate these threats from clutter in an operational environment. Current systems have implemented ground-penetrating radar (GPR) and electromagnetic induction (EMI) sensors. The detection performance of these systems is assessed in field testing, where algorithms are used to determine when a buried threat has been encountered [1]. Similar to work done by Rosen and Ayers [2], this paper focuses on developing a method to study EMI sensor performance independent of any aided target recognition (ATR) algorithm used. Rosen and Ayers developed a method and a simple metric for assessing the mine-detection capabilities of down-looking GPR systems before an ATR algorithm is applied. This paper reports the development of two metrics for a wide-band EMI sensor based on the method used by Rosen and Ayers. In this initial effort, the values of the metrics developed are presented over different targets, and observations are made regarding potential use of this metric.

In this paper, radar detection via compressive sensing is explored. Compressive sensing is a new theory of sampling which allows the reconstruction of a sparse signal by sampling at a much lower rate than the Nyquist rate. By using this technique in radar, the use of matched filter can be eliminated and high rate sampling can be replaced with low rate sampling. In this paper, compressive sensing is analyzed by applying varying factors such as noise and different measurement matrices. Different reconstruction algorithms are compared by generating ROC curves to determine their detection performance. We conduct simulations for a 64-length signal with 3 targets to determine the effectiveness of each algorithm in varying SNR. We also propose a simplified version of Orthogonal Matching Pursuit (OMP). Through numerous simulations, we find that a simplified version of Orthogonal Matching Pursuit (OMP), can give better results than the original OMP in noisy environments when sparsity is highly over estimated, but does not work as well for low noise environments.

This paper describes the study of a through-the-wall radar system for three-dimensional (3-D) building imaging, based on computer simulations. Two possible configurations are considered, corresponding to an airborne spotlight and a ground-based strip-map geometry. The paper details all the steps involved in this analysis: creating the computational meshes, calculating the radar signals scattered by the target, forming the radar images, and processing the images for visualization and interpretation. Particular attention is given to the scattering phenomenology and its dependence on the system geometry. The images are created via the backprojection algorithm and further processed using a constant falsealarm rate (CFAR) detector. We discuss methods of 3-D image visualization and interpretation of the results.

In this paper we apply a sparse signal recovery technique for synthetic aperture radar (SAR) image formation from interrupted phase history data. Timeline constraints imposed on multi-function modern radars result in interrupted SAR data collection, which in turn leads to corrupted imagery that degrades reliable change detection. In this paper we extrapolate the missing data by applying the basis pursuit denoising algorithm (BPDN) in the image formation step, effectively, modeling the SAR scene as sparse. We investigate the effects of regular and random interruptions on the SAR point spread function (PSF), as well as on the quality of both coherent (CCD) and non-coherent (NCCD) change detection. We contrast the sparse reconstruction to the matched filter (MF) method, implemented via Fourier processing with missing data set to zero. To illustrate the capabilities of the gap-filling sparse reconstruction algorithm, we evaluate change detection performance using a pair of images from the GOTCHA data set.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

This paper details a Video SAR (Synthetic Aperture Radar) mode that provides a persistent view of a scene centered at the Motion Compensation Point (MCP). The radar platform follows a circular flight path. An objective is to form a sequence of SAR images while observing dynamic scene changes at a selectable video frame rate. A formulation of backprojection meets this objective. Modified backprojection equations take into account changes in the grazing angle or squint angle that result from non-ideal flight paths. The algorithm forms a new video frame relying upon much of the signal processing performed in prior frames. The method described applies an appropriate azimuth window to each video frame for window sidelobe rejection. A Cardinal Direction Up (CDU) coordinate frame forms images with the top of the image oriented along a given cardinal direction for all video frames. Using this coordinate frame helps characterize a moving target’s target response. Generation of synthetic targets with linear motion including both constant velocity and constant acceleration is described. The synthetic target video imagery demonstrates dynamic SAR imagery with expected moving target responses. The paper presents 2011 flight data collected by General Atomics Aeronautical Systems, Inc. (GA-ASI) implementing the video SAR mode. The flight data demonstrates good video quality showing moving vehicles. The flight imagery demonstrates the real-time capability of the video SAR mode. The video SAR mode uses a circular shift register of subapertures. The radar employs a Graphics Processing Unit (GPU) in order to implement this algorithm.

In order to obtain the non-overlapping and high-quality reconstructed image, this paper analyzes the system parameters in digital holographic microscopy. Nowadays a few scholars have analyzed the system parameters which need to satisfy the sampling theorem and spectrum separation conditions. In this paper, not only the sampling theorem and spectrum separation but also the size relationship between the reconstructed plane and the magnified image are studied. Then relationships of system parameters are proposed. First, the maximum object size is directly proportional to the wavelength and microscope objective focal length, inversely proportional to the sampling interval. Second, the minimum magnification is described accurately. Finally, the paper gives the range of recoding distance. Experiments further demonstrate the proposed conclusion’s validity.

Security holograms (SH) are widely used for authenticity protection of document and product due to difficulties of such a protection mark falsification. Mass production of SH uses widespread technology of hot foil or lavsan paper stamping. The quality of holograms significantly depends on perfection of nickel master-matrix that is used in stamping equipment. We represent the method for automated quality inspection of nickel mastermatrix based on digital processing of its surface relief images. Proposed processing algorithm is based on combination of image spatial frequency analysis and image matching using distortion invariant correlation filters. The results of our method application for real master-matrix inspection are shown in this paper.

Security holograms (SH) are perspective for document and product authenticity protection due to difficulties of such a protection mark falsification. Mass production of SH uses widespread technology of hot foil or lavsan paper stamping. The quality of holograms significantly depends on perfection of nickel master-matrix that is used in stamping equipment. We represent the method of automatic quality inspection of nickel master-matrix based on digital processing of its surface relief microphotographs. Proposed processing algorithm is based on combination of image spatial frequency analysis and image matching using distortion invariant correlation filters. The results of our method application for real SH master-matrices inspection are shown in this paper.