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Conference on Enabling Photonics Technologies for Defense, Security, and Aerospace Applications VI

作者： Bhooplapur, Sharad Akbulut, Mehmetcan Quinlan, Franklyn Delfyett, Peter J. Univ Cent Florida CREOL Coll Opt & Photon Orlando FL 32816 USA Fibertek Inc Herndon VA 20170 USA Mailcode 847 80 Boulder CO 80305 USA

ISBN: (纸本)9780819481641

A novel scheme for recognition of electronic bit-sequences is demonstrated. Two electronic bit-sequences that are to be compared are each mapped to a unique code from a set of Walsh-Hadamard codes. The codes are then encoded in parallel on the spectral phase of the frequency comb lines from a frequency-stabilized mode-locked semiconductor laser. Phase encoding is achieved by using two independent spatial light modulators based on liquid crystal arrays. Encoded pulses are compared using interferometric pulse detection and differential balanced photodetection. Orthogonal codes eight bits long are compared, and matched codes are successfully distinguished from mismatched codes with very low error rates, of around 10(-18). This technique has potential for high-speed, high accuracy recognition of bit-sequences, with applications in keyword searches and internet protocol packet routing.

关键词： optical pattern recognition semiconductor frequency comb source

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Graph classification and clustering based on vector space embedding /

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2010年

作者： Riesen Kaspar.

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recognition and tracking of target based on three-dimensional joint transform correlation

Recognition and tracking of target based on three-dimensiona...

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International Conference on optical Instruments and Technology - optical Systems and Optoelectronic Instruments

作者： Zhang, Huihua Xu, Zhongbao Zhang, Shuang Hubei Univ Technol Sch Mech Engn Wuhan 430068 Peoples R China

ISBN: (纸本)9780819474001

Classical joint transform correlator (JTC) has been widely used in pattern recognition and target tracking. However, when a real-time three-dimensional (3-D) object is captured as a two-dimensional (2-D) image, the key depth information for discriminating different objects is lost. In some cases, two dissimilar objects may appear to be the same appearance in their 2-D space. In this paper, a novel optical-electrical hybrid JTC is presented by analyzing a series of 2-D projections of the 3-D tested objects from different points of view. After encoding the key depth information into the 2-D power spectrum as the phase factor of the complex amplitude, we can obtain the 3-D joint power spectrum (JPS) and the 3-D joint correlation output, respectively. The presence of the 3-D object and its precise spatial position can be recognized by analyzing the correlation peak. Simultaneously, in order to reconstruct the original target images from the finite discrete spectrum, the space parameters of the system are founded based on discussing the relation between the number of the 2-D projections and the quality of the correlation output. Furthermore, the way to overcome the shortcomings in the correlation output, such as a low correlation peak, a low peak-to-sidelobe ratio and a wide correlation peak width, are discussed. The simulation result shows that the proposed method is effective for recognition and tracking the targets distributed in 3-D space.

关键词： optical pattern recognition 3-D object recognition joint transform correlation 3-D Fourier transform optical-electrical hybrid process

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Template Matching Techniques in Computer Vision 1

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2009年

作者： Roberto Brunelli

ISBN: (数字)9780470744048

ISBN: (纸本)9780470517062

The detection and recognition of objects in images is a key research topic in the computer vision community. Within this area, face recognition and interpretation has attracted increasing attention owing to the possibility of unveiling human perception mechanisms, and for the development of practical biometric systems. This book and the accompanying website, focus on template matching, a subset of object recognition techniques of wide applicability, which has proved to be particularly effective for face recognition applications. Using examples from face processing tasks throughout the book to illustrate more general object recognition approaches, Roberto Brunelli: examines the basics of digital image formation, highlighting points critical to the task of template matching; presents basic and advanced template matching techniques, targeting grey-level images, shapes and point sets; discusses recent pattern classification paradigms from a template matching perspective; illustrates the development of a real face recognition system; explores the use of advanced computer graphics techniques in the development of computer vision algorithms. Template Matching Techniques in Computer Vision is primarily aimed at practitioners working on the development of systems for effective object recognition such as biometrics, robot navigation, multimedia retrieval and landmark detection. It is also of interest to graduate students undertaking studies in these areas.

关键词： Image processing Template matching (Digital image processing) Computer vision Image analysis optical pattern recognition

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Effects of threshold on multiple-target detection by using a modified amplitude-modulated joint transform correlator

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optical ENGINEERING 2008年第1期47卷

作者： Kaewkasi, Pitchaya Widjaja, Joewono Uozumi, Jun Suranaree Univ Technol Inst Sci Nakhon Ratchasima 30000 Thailand Hokkai Gakuen Univ Fac Engn Sapporo Hokkaido 0640926 Japan

Effects of the threshold value on the multiple-target detection performance of a modified amplitude-modulated joint transform correlator are studied on the basis of computer simulations, using human fingerprint and face images. Correlation outputs are quantitatively measured by means of a primary-to-seconclary peak ratio and a peak-to-correlation-deviation ratio. The simulation results reveal that the detection of high-contrast targets can be optimized by using a low-threshold. In the case of low-contrast targets, the optimization depends on spatial-frequency contents and noise. (C) 2008 Society of Photo-optical Instrumentation Engineers.

关键词： multiple-target detection modified amplitude-modulated joint transform correlator detection performance optical pattern recognition

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pattern recognition using Gaussian-filtered, shifted phase-encoded fringe-adjusted joint transform correlation

Pattern recognition using Gaussian-filtered, shifted phase-e...

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Conference on optical pattern recognition XIX

作者： Islam, Mohammed Nazrul Alam, Mohammad S. Asari, K. Vijayan Karim, Mohammad A. Old Dominion Univ Res Fdn Norfolk VA 23529 USA Univ S Alabama Dept Elect & Comp Engn Mobile AL 36688 USA Old Dominion Univ Dept Elect & Comp Engn Norfolk VA 23529 USA Old Dominion Univ Res Off Norfolk VA 23529 USA

ISBN: (纸本)9780819471680

pattern recognition for real-time applications requires the detection scheme be a simple architecture, fast in operation, able to detect all the potential targets without generating any false alarms, and invariant to noise and distortion. Though several target detection algorithms have been proposed in the literature over the years, but most of them are found to be not as efficient in meeting all the above-mentioned objective requirements. A new Gaussian-filtered, shifted phase-encoded fringe-adjusted joint transform correlation technique has been developed in this paper for an optical pattern recognition system. The input noisy image is first filtered by using a Gaussian filter, which helps in overcoming the effect of background noise and distortions. Then the filtered image is correlated with the reference image using the proposed joint transform correlator, which eliminates the problems of duplicate correlation heights, false alarms and low discrimination ratio. The architecture involves optical devices including lenses and spatial light modulators, which guarantees the very fast operation required for real-time applications. Computer simulation results show that the algorithm can successfully discriminate between targets and non-targets contained in the input scene even in the presence of noise and can also make the best utilization of the correlation space.

关键词： optical pattern recognition Gaussian filter joint transform correlation target detection

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Semantic representation and recognition of human activities

Semantic representation and recognition of human activities

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作者： Ryoo, Michael Sahngwon The University of Texas at Austin

学位级别：D.Eng.

This dissertation describes a methodology for automated recognition of complex human activities. The dissertation presents a general framework which reliably recognizes various types of high-level human activities including human actions, human-human interactions, human-object interactions, and group activities. Our approach is a description-based approach, which enables a user to encode the structure of a high-level human activity as a formal representation. recognition of human activities is done by semantically matching constructed representations with actual observations. The methodology uses a context-free grammar (CFG) based representation scheme as a formal syntax for representing composite activities. Our CFG-based representation enables us to define complex human activities based on simpler activities or movements. We have constructed a hierarchical framework which automatically matches activity representations with input observations. In the low-level of the system, image sequences are processed to extract poses and gestures. Based on the recognition of gestures, the high-level of the system hierarchically recognizes complex occurring human activities by searching for gestures that satisfies the temporal, spatial, and logical structure described in the representation. The concept of hallucinations and a probabilistic semantic-level recognition algorithm is introduced to cope with imperfect lower-layers. As a result, the system recognizes human activities including ‘fighting’, ‘assault’, ‘a person leaving a suitcase’, and ‘a group of thieves stealing an object from owners’, which are high-level activities that previous systems had difficulties. The experimental results show that our system reliably recognizes sequences of various types of complex human activities with a high recognition rate.

关键词： optical pattern recognition

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Noise elimination methods in topological pattern recognition

Noise elimination methods in topological pattern recognition

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Conference on optical pattern recognition XIX

作者： Hu, Chialun J. Univ Colorado Dept Elect & Comp Engn Boulder CO 80301 USA

ISBN: (纸本)9780819471680

As we published in the last three years, we can use the continuity threshold and the geometric projection methods to eliminate the background noise and the cloud-obscuring noise in an edge-detected 2D color picture for the topological pattern recognition system developed by the author. Preliminary computer experiments showed that the background noise elimination is thorough and the reconstruction of the obscured part of the original image is 90%+ accurate.

关键词： Analog electronics pattern recognition Raster graphics Reconstruction algorithms Binary data Chaos Computer engineering Computing systems optical pattern recognition Visualization

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A technique of optical pattern recognition with rotational invariance

A technique of optical pattern recognition with rotational i...

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5th Iberoamerican Meeting on Optics/8th Latin American Meeting on Optics, Lasers, and Their Applications

作者： Toto-Arellano, NI Camacho-Basilio, G Univ Autonoma Puebla Fac Ciencias Fis Matemat Puebla 72000 Mexico

ISBN: (纸本)081945575X

The optical pattern recognition system of joint transform correlation has a disadvantage. It doesn't work under rotation of test object [1]. In this work we show the experimental results of a technique for rotational invariant optical recognition which is based on a ring detector acting as filter. This correlator has the disadvantage of not present scale invariance of the objects under test. In addition, a theoretical analysis and simulation results are illustrated here with the use of an advanced mathematics software package.

关键词： optical pattern recognition image processing

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recognition and tracking of target based on three-dimensional joint transform correlation

Recognition and tracking of target based on three-dimensiona...

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2008 International Conference on optical Instruments and Technology

作者： Huihua,ZHANG~(1,2) Zhongbao,XU~(1,2) Shuang,ZHANG~(1,2) (1.School of Mechanical Engineering,Hubei University of Technology,Wuhan 430068,China 2.The Key Laboratory of Modern Manufacturing Quantity Engineering of Hubei Province, Wuhan 430068,China)

Classical joint transform correlator(JTC)has been widely used in pattern recognition and target ***, when a real-time three-dimensional(3-D)object is captured as a two- dimensional(2-D)image,the key depth information for discriminating different objects is *** some cases,two dissimilar objects may appear to be the same appearance in their 2-D *** this paper,a novel optical-electrical hybrid JTC is presented by analyzing a series of 2-D projections of the 3-D tested objects from different points of *** encoding the key depth information into the 2-D power spectrum as the phase factor of the complex amplitude,we can obtain the 3-D joint power spectrum(JPS)and the 3-D joint correlation output,*** presence of the 3-D object and its precise spatial position can be recognized by analyzing the correlation ***,in order to reconstruct the original target images from the finite discrete spectrum,the space parameters of the system are founded based on discussing the relation between the number of the 2-D projections and the quality of the correlation ***,the way to overcome the shortcomings in the correlation output,such as a low correlation peak,a low peak-to-sidelobe ratio and a wide correlation peak width,are *** simulation result shows that the proposed method is effective for recognition and tracking the targets distributed in 3-D space.

关键词： optical pattern recognition 3-D object recognition joint transform correlation 3-D Fourier transform optical-electrical hybrid process

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