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Is spectral reflectance of the face a reliable biometric?

OPTICS EXPRESS 2015年第12期23卷 15160-15173页

作者： Uzair, Muhammad Mahmood, Arif Shafait, Faisal Nansen, Christian Mian, Ajmal Univ Western Australia Comp Sci & Software Engn Crawley WA 6009 Australia Univ Calif Davis Dept Entomol & Nematol Davis CA 95616 USA

Over a decade ago, Pan et al. [IEEE TPAMI 25, 1552 (2003)] performed face recognition using only the spectral reflectance of the face at six points and reported around 95% recognition rate. Since their database is private, no one has been able to replicate these results. Moreover, due to the unavailability of public datasets, there has been no detailed study in the literature on the viability of facial spectral reflectance for person identification. In this study, we introduce a new public database of facial spectral reflectance profiles measured with a high precision spectrometer. For each of the 40 subjects, spectral reflectance was measured at the same six points as Pan et al. [IEEE TPAMI 25, 1552 (2003)] in multiple sessions and with time lapse. Furthermore, we sample the facial spectral reflectance from two public hyperspectral face image datasets and analyzed the data using state of the art face classification techniques. The best performing classifier achieved the maximum rank-1 identification rate of 53.8%. We conclude that facial spectral reflectance alone is not a reliable biometric for unconstrained face recognition. (C) 2015 Optical Society of America.

关键词： Face recognition Fiber optic cables Hyperspectral imaging image recognition algorithms Reflectance spectroscopy Retina scanning

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Illuminant direction estimation for a single image based on local region complexity analysis and average gray value

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APPLIED OPTICS 2014年第2期53卷 226-236页

作者： Yi, Jizheng Mao, Xia Chen, Lijiang Xue, Yuli Compare, Angelo Beihang Univ Sch Elect & Informat Engn Beijing 100191 Peoples R China Univ Bergamo Dept Human Sci I-24129 Bergamo Italy

Illuminant direction estimation is an important research issue in the field of image processing. Due to low cost for getting texture information from a single image, it is worthwhile to estimate illuminant direction by employing scenario texture information. This paper proposes a novel computation method to estimate illuminant direction on both color outdoor images and the extended Yale face database B. In our paper, the luminance component is separated from the resized YCbCr image and its edges are detected with the Canny edge detector. Then, we divide the binary edge image into 16 local regions and calculate the edge level percentage in each of them. Afterward, we use the edge level percentage to analyze the complexity of each local region included in the luminance component. Finally, according to the error function between the measured intensity and the calculated intensity, and the constraint function for an infinite light source model, we calculate the illuminant directions of the luminance component's three local regions, which meet the requirements of lower complexity and larger average gray value, and synthesize them as the final illuminant direction. Unlike previous works, the proposed method requires neither all of the information of the image nor the texture that is included in the training set. Experimental results show that the proposed method works better at the correct rate and execution time than the existing ones. (C) 2014 Optical Society of America

关键词： Computation methods Edge detection image processing image recognition algorithms Light properties Light sources

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Dictionaries for image and video-based face recognition [Invited]

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JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS image SCIENCE AND VISION 2014年第5期31卷 1090-1103页

作者： Patel, Vishal M. Chen, Yi-Chen Chellappa, Rama Phillips, P. Jonathon Univ Maryland UMIACS Ctr Automat Res College Pk MD 20742 USA Natl Inst Stand & Technol Gaithersburg MD 20899 USA

In recent years, sparse representation and dictionary-learning-based methods have emerged as powerful tools for efficiently processing data in nontraditional ways. A particular area of promise for these theories is face recognition. In this paper, we review the role of sparse representation and dictionary learning for efficient face identification and verification. Recent face recognition algorithms from still images, videos, and ambiguously labeled imagery are reviewed. In particular, discriminative dictionary learning algorithms as well as methods based on weakly supervised learning and domain adaptation are summarized. Some of the compelling challenges and issues that confront research in face recognition using sparse representations and dictionary learning are outlined. (C) 2014 Optical Society of America

关键词： Face recognition Feature extraction image processing image recognition algorithms Iris Saliency

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Automated alignment system for optical wireless communication systems using image recognition

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OPTICS LETTERS 2014年第13期39卷 4045-4048页

作者： Brandl, Paul Weiss, Alexander Zimmermann, Horst Vienna Univ Technol Inst Electrodynam Microwave & Circuit Engn A-1040 Vienna Austria

In this Letter, we describe the realization of a tracked line-of-sight optical wireless communication system for indoor data distribution. We built a laser-based transmitter with adaptive focus and ray steering by a microelectromechanical systems mirror. To execute the alignment procedure, we used a CMOS image sensor at the transmitter side and developed an algorithm for image recognition to localize the receiver's position. The receiver is based on a self-developed optoelectronic integrated chip with low requirements on the receiver optics to make the system economically attractive. With this system, we were able to set up the communication link automatically without any back channel and to perform error-free (bit error rate < 10(-9)) data transmission over a distance of 3.5 m with a data rate of 3 Gbit/s. (C) 2014 Optical Society of America

关键词： image recognition image recognition algorithms Laser beams Microelectromechanical systems Optical testing Optical wireless communication

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Optical magnetometry of single NV center scanning local magnetic field in micro fluid devices

Optical magnetometry of single NV center scanning local magn...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Lim, Kangmook Shapiro, Benjamin Taylor, Jacob Waks, Edo Univ Maryland Dept Elect & Comp Engn College Pk MD 20742 USA Univ Maryland Inst Res Elect & Appl Phys College Pk MD 20742 USA Univ Maryland Fischell Dept Bioengn College Pk MD 20742 USA Univ Maryland Inst Syst Res College Pk MD 20742 USA Univ Maryland Joint Quantum Inst NIST College Pk MD 20742 USA

By combining magnetic nanoparticle 3D positioning system and NV ESR measurements in micro-fluid device, we demonstrate sensing of magnetic fringe field of a magnetic bead repeatedly displaced and mapping field profile... 详细信息

ISBN: (纸本)9781557529992

关键词： CCD cameras Electric fields image recognition algorithms Magnetic fields Nitrogen vacancy centers Photon counting Zeeman effect (260.7490) Coherent optical effects (270.1670) Quantum detectors (270.5570)

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A de-illumination scheme for face recognition based on fast decomposition and detail feature fusion

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OPTICS EXPRESS 2013年第9期21卷 11294-11308页

作者： Zhou, Yi Zhou, Sheng-Tong Zhong, Zuo-Yang Li, Hong-Guang Shanghai Jiao Tong Univ State Key Lab Mech Syst & Vibrat Shanghai 200240 Peoples R China

Almost all the face recognition algorithms are unsatisfied due to illumination variation. Feature with high frequency represents the face intrinsic structure according to the common assumption that illumination varies slowly and the face intrinsic feature varies rapidly. In this paper, we will propose an adaptive scheme based on FBEEMD and detail feature fusion. FBEEMD is a fast version of BEEMD without time-consuming surface interpolation and iteration computation. It can decompose an image into sub-images with high frequency matching detail feature and sub-images with low frequency corresponding to contour feature. However, it is difficult to determine by quantitative analysis that which sub-images with high frequency can be used for reconstructing an illumination-invariant face. Thus, two measurements are proposed to calculate weights for quantifying the detail feature. With this fusion technique, one can reconstruct a more illumination-neutral facial image to improve face recognition rate. Verification experiments using classical recognition algorithms are tested with Yale B, PIE and FERET databases. The encouraging results show that the proposed scheme is very effective when dealing with face images under variable lighting condition. (c) 2013 Optical Society of America

关键词： Adaptive imaging Face recognition Feature extraction image processing image recognition algorithms Optical fields

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Spectral optimized asymmetric segmented phase-only correlation filter

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APPLIED OPTICS 2012年第14期51卷 2638-2650页

作者： Leonard, I. Alfalou, A. Brosseau, C. Univ Brest Lab Sci & Tech Informat Commun & Connaissance Univ Europeenne Bretagne F-29238 Brest 3 France ISEN Dept Vis Lab Rech F-29228 Brest 2 France

We suggest a new type of optimized composite filter, i.e., the asymmetric segmented phase-only filter (ASPOF), for improving the effectiveness of a VanderLugt correlator (VLC) when used for face identification. Basically, it consists in merging several reference images after application of a specific spectral optimization method. After segmentation of the spectral filter plane to several areas, each area is assigned to a single winner reference according to a new optimized criterion. The point of the paper is to show that this method offers a significant performance improvement on standard composite filters for face identification. We first briefly revisit composite filters [adapted, phase-only, inverse, compromise optimal, segmented, minimum average correlation energy, optimal trade-off maximum average correlation, and amplitude-modulated phase-only (AMPOF)], which are tools of choice for face recognition based on correlation techniques, and compare their performances with those of the ASPOF. We illustrate some of the drawbacks of current filters for several binary and grayscale image identifications. Next, we describe the optimization steps and introduce the ASPOF that can overcome these technical issues to improve the quality and the reliability of the correlation-based decision. We derive performance measures, i.e., PCE values and receiver operating characteristic curves, to confirm consistency of the results. We numerically find that this filter increases the recognition rate and decreases the false alarm rate. The results show that the discrimination of the ASPOF is comparable to that of the AMPOF, but the ASPOF is more robust than the trade-off maximum average correlation height against rotation and various types of noise sources. Our method has several features that make it amenable to experimental implementation using a VLC. (C) 2012 Optical Society of America

关键词： Face recognition Fourier transforms image recognition algorithms Joint transform correlators Phase only filters Target tracking

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Face recognition performance with superresolution

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APPLIED OPTICS 2012年第18期51卷 4250-4259页

作者： Hu, Shuowen Maschal, Robert Young, S. Susan Hong, Tsai Hong Phillips, P. Jonathon USA Res Lab Adelphi MD 20783 USA NIST Gaithersburg MD 20899 USA

With the prevalence of surveillance systems, face recognition is crucial to aiding the law enforcement community and homeland security in identifying suspects and suspicious individuals on watch lists. However, face recognition performance is severely affected by the low face resolution of individuals in typical surveillance footage, oftentimes due to the distance of individuals from the cameras as well as the small pixel count of low-cost surveillance systems. Superresolution image reconstruction has the potential to improve face recognition performance by using a sequence of low-resolution images of an individual's face in the same pose to reconstruct a more detailed high-resolution facial image. This work conducts an extensive performance evaluation of superresolution for a face recognition algorithm using a methodology and experimental setup consistent with real world settings at multiple subject-to-camera distances. Results show that superresolution image reconstruction improves face recognition performance considerably at the examined midrange and close range.

关键词： Face recognition Fourier transforms image enhancement image recognition algorithms image reconstruction Superresolution

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Decision optimization for face recognition based on an alternate correlation plane quantification metric

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OPTICS LETTERS 2012年第9期37卷 1562-1564页

作者： Alfalou, A. Brosseau, C. Katz, P. Alam, M. S. Univ Brest Univ Europeenne Bretagne Lab STICC F-29238 Brest 3 France ISEN Brest Dept Optoelect L BISEN F-29228 Brest 2 France Univ S Alabama Dept Elect & Comp Engn Mobile AL 36688 USA

We consider a new approach for enhancing the discrimination performance of the VanderLugt correlator. Instead of trying to optimize the correlation filter, or propose a new decision correlation peak detection criterion, we propose herein to denoise the correlation plane before applying the peak-to-correlation energy (PCE) criterion. For that purpose, we use a linear functional model to express a given correlation plane as a linear combination of the correlation peak, noise, and residual components. The correlation peak is modeled using an orthonormalized function and the singular value decomposition method. A set of training correlation planes is then selected to create the correlation noise components. Finally, an optimized correlation plane is reconstructed while discarding the noise components. Independently of the filter correlation used, this technique denoises the correlation plane by lowering the correlation noise magnitude in case of true correlation and decreases the false alarm rate when the target image does not belong to the desired class. Test results are presented, using a composite filter and a face recognition application, to verify the effectiveness of the proposed technique. (C) 2012 Optical Society of America

关键词： Composite materials Correlators Face recognition image recognition algorithms Noise reduction Phase only filters

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Sparsity-motivated automatic target recognition

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APPLIED OPTICS 2011年第10期50卷 1425-1433页

作者： Patel, Vishal M. Nasrabadi, Nasser M. Chellappa, Rama Univ Maryland Dept Elect & Comp Engn Ctr Automat Res College Pk MD 20742 USA US Army Res Lab Adelphi MD 20783 USA

We present an automatic target recognition algorithm using the recently developed theory of sparse representations and compressive sensing. We show how sparsity can be helpful for efficient utilization of data for target recognition. We verify the efficacy of the proposed algorithm in terms of the recognition rate and confusion matrices on the well known Comanche (Boeing-Sikorsky, USA) forward-looking IR data set consisting of ten different military targets at different orientations. (C) 2011 Optical Society of America

关键词： Attenuated total reflectance Forward looking infrared image quality image recognition algorithms Neural networks Synthetic aperture radar

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