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International Conference on Intelligent Control and Information processing (ICICIP)

作者： Jianguo Liu Zhenbing Liu Chao Pan State Key Laboratory for Multi-spectral Information Processing Technology Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

The Discrete Fourier transform (DFT) is an important tool in digital signal processing. In this paper, a novel approach to DFT is proposed. The computation of DFT is transformed to the computation of the first-order moments by the simple mathematical deductions. It is well known that the first-order moments can be computed efficiently using only additions. An efficient systolic array is designed to implement DFT. The comparison with the existing methods shows the advantages of our method. The approach is also applicable to DFT inverses.

关键词： Discrete Fourier transforms Arrays Clocks Algorithm design and analysis Complexity theory Signal processing algorithms

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Ethnicity classification based on gait using multi-view fusion

Ethnicity classification based on gait using multi-view fusi...

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IEEE Computer Society Conference on Computer Vision and pattern recognition Workshops (CVPRW)

作者： De Zhang Yunhong Wang Bir Bhanu Center for Research in Intelligent Systems University of California Riverside CA USA Intelligent Recognition and Image Processing Laboratory Beihang University Beijing China

The determination of ethnicity of an individual, as a soft biometrics, can be very useful in a video-based surveillance system. Currently, face is commonly used to determine the ethnicity of a person. Up to now, gait has been used for individual recognition and gender classification but not for ethnicity determination. This paper focuses on the ethnicity determination based on fusion of multi-view gait. Gait Energy image (GEI) is used to analyze the recognition power of gait for ethnicity. Feature fusion, score fusion and decision fusion from multiple views of gait are explored. For the feature fusion, GEI images and camera views are put together to render a third-order tensor (x; y; view). A multilinear principal component analysis (MPCA) is used to extract features from tensor objects which integrate all views. For the score fusion, the similarity scores measured from single views are combined with a weighted SUM rule. For the decision fusion, ethnicity classification is realized on each individual view first. The classification results are then combined to make the final determination with a majority vote rule. A database of 36 walking people (East Asian and South American) was acquired from 7 different camera views. The experimental results show that ethnicity can be determined from human gait in video automatically. The classification rate is improved by fusing multiple camera views and a comparison among different fusion schemes shows that the MPCA based feature fusion performs the best.

关键词： Cameras Tensile stress Biometrics Surveillance image analysis image recognition Rendering (computer graphics) Principal component analysis Feature extraction Voting

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A watermark technology of print-scan resilient based on DFT transform

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Beijing Gongye Daxue Xuebao/Journal of Beijing University of Technology 2010年第SUPPL. 1期36卷 113-117页

作者： Zou, Jian-Cheng Si, Jian-Min Institute of Image Processing and Pattern Recognition North China University of Technology Beijing 100144 China

A method of printing and certificate forgery based on digital watermarking is presented. This method embeds watermark in the DFT domain using the principles that middle and low frequency coefficients have little changes in print-scan process, and using HOUGH transform for image correction to resist rotation attacks when extracting watermarks. The experimental results show that this method has strong robustness to first print-scan images, which can be detected right watermarks, while for the second print-scan images robustness drops about 20%. Therefore the algorithm can be used to identify the authenticity of printing and certificates by the correction of the watermarks and can be used to all types of copyright protection and certificates security.

关键词： Copyrights

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A new replica selection strategy based on combination algorithm

A new replica selection strategy based on combination algori...

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International Conference on Internet Technology and Applications, ITAP 2010

作者： Guo, Zheng-Wei Li, Ning Li, Hui Shi, Nan College of Computer and Information Engineering Institute of Image Processing and Pattern Recognition Henan University Kaifeng Henan China College of Computer and Information Engineering Henan University Kaifeng Henan China

ISBN: (纸本)9781424451432

In the data grid environment, when users access to files, how to select the best site to obtain files from multiple replicas and reach the highest QOS(quality of service) in the cost of same price is a problem that need to be studied urgently, that is replica selection. In this paper, it proposes a new combination algorithm based on genetic algorithm and ant algorithm, which not only solves the inefficient disadvantage of genetic algorithm, but also solves the problem of solving problems slowly in the early period in ant algorithm. This strategy is analyzed and simulated by data grid simulator OptorSim, and the results show that this new algorithm can be effective in reducing data access latency, improve data access speed, speed up job completion time, and achieve load balancing. ©2010 IEEE.

关键词： Genetic algorithms

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A novel method of fingerprint minutiae extraction based on Gabor phase

A novel method of fingerprint minutiae extraction based on G...

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IEEE International Conference on image processing

作者： Xin Gao Xiaoguang Chen Jia Cao Zirui Deng Chongjin Liu Jufu Feng Key Laboratory of Machine Perception MOE Department of Machine Intelligence School of Electronics Engineering and Computer Science Peking University Beijing China Institute of Image Processing and Pattern Recognition North-China University of Technology Beijing China

In this paper, a novel method of fingerprint minutiae extraction on grey-scale images is proposed based on the Gabor phase field. The novelty of our approach is that the proposed algorithm is performed on the transform domain, i.e. the Gabor phase field of the fingerprint image. This is different from most existing minutiae extraction methods, in which the minutiae are usually extracted from the binarized and thinned fingerprint image. Experimental results on benchmark data sets demonstrate that the proposed algorithm has promising performances.

关键词： Pixel Feature extraction image quality Fingerprint recognition Detectors Frequency estimation Software algorithms

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Second order morphology algorithm for IR small target enhancement in sea clutter background

Second order morphology algorithm for IR small target enhanc...

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International Conference on Optics Photonics and Energy Engineering (OPEE)

作者： Zhou Xiao Mou xingang Zhang guilin National Key Laboratory of Science and Technology On Multi-spectral Information Processing Technologies Institute For Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424452347;9781424452354;9781424452361

The framework of a second order morphology algorithm is proposed to enhance the dim small infrared target in sea clutter background with strong detector noise. First, a morphological filters bank is given. Each filter in the bank is designed to suppress its corresponding type texture. The second order process can be accomplished in two steps. The original infrared image is first filtered using each filter separately, and then the first order result is obtained by the combination of the filtered result images. The other step is essentially the same as the first one except the combination manner of the filtered result images. Second, the traditional SNR gain based evaluation of different small target enhancement algorithms is examined and a more reasonable method based on the distance between the target and the maximal background (DTMB) is described in this paper. Third, using the new evaluation method, the comparison is given by experiment through a sequence of infrared images with a dim small target. Experimental results demonstrate that the new proposed algorithm performs better in sea clutter background with strong detector noise than the traditional ones.

关键词： Morphology Filter bank Infrared detectors Nonlinear filters Background noise Infrared imaging Shape Working environment noise Optical filters Photonics

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Moving object segmentation based on new likelihood functions

Moving object segmentation based on new likelihood functions

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IEEE International Symposium on Intelligent Signal processing and Communication Systems (ISPACS)

作者： Xiang Zhang Zhi Liu Jie Yang Institute of Image Processing and Patter Recognition Shanghai Jiaotong University China Key Laboratory of Advanced Display and System Application Ministry of Education Shanghai University China

Accurate segmentation of moving objects from a video sequence is still a difficult task. A moving object segmentation method is proposed in this paper to deal with the segmentation splits and defects. First, it is claimed that the confusion point is one reason for the segmentation inaccuracy, and corresponding solution is also presented. According to the solution, new likelihood functions are proposed to compute membership probabilities, which are then used for final segmentation within an energy minimization framework. Unlike related algorithms which compute membership probabilities using kernel density estimation, the proposed method models the membership probabilities as functions with kernel density estimation as the independent variable. Experiments show that improved results are generated by the proposed likelihood functions.

关键词： Radio access networks

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General moving objects recognition method based on graph embedding dimension reduction algorithm

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2009年第7期10卷 976-984页

作者： Yi ZHANG Jie YANG Kun LIU Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China

Effective and robust recognition and tracking of objects are the key problems in visual surveillance systems. Most existing object recognition methods were designed with particular objects in mind. This study presents a general moving objects recognition method using global features of targets. Targets are extracted with an adaptive Gaussian mixture model and their silhouette images are captured and unified. A new objects silhouette database is built to provide abundant samples to train the subspace feature. This database is more convincing than the previous ones. A more effective dimension reduction method based on graph embedding is used to obtain the projection eigenvector. In our experiments, we show the effective performance of our method in addressing the moving objects recognition problem and its superiority compared with the previous methods.

关键词： Moving objects recognition Adaptive Gaussian mixture model Principal component analysis Linear discriminant analysis Marginal Fisher analysis

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Bayesian moving object detection in dynamic scenes using an adaptive foreground model

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2009年第12期10卷 1750-1758页

作者： Sheng-yang YU Fang-lin WANG Yun-feng XUE Jie YANG Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China

Accurate detection of moving objects is an important step in stable tracking or recognition. By using a nonparametric density estimation method over a joint domain-range representation of image pixels, the correlation between neighboring pixels can be used to achieve high levels of detection accuracy in the presence of dynamic background. However, color similarity between foreground and background will cause many foreground pixels to be misclassified. In this paper, an adaptive foreground model is exploited to detect moving objects in dynamic scenes. The foreground model provides an effective description of foreground by adaptively combining the temporal persistence and spatial coherence of moving objects. Building on the advantages of MAP-MRF (the maximum a posteriori in the Markov random field) decision framework, the proposed method performs well in addressing the challenging problem of missed detection caused by similarity in color between foreground and background pixels. Experimental results on real dynamic scenes show that the proposed method is robust and efficient.

关键词： Moving object detection Foreground model Kernel density estimation （KDE） MAP-MRF estimation

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I2T: image parsing to text description

I2T: Image parsing to text description

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作者： Yao, Benjamin Z. Yang, Xiong Lin, Liang Lee, Mun Wai Zhu, Song-Chun Lotus Hill Institute Ezhou 436000 China Los Angeles CA 90095 United States Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Laboratory of Intelligent Information Processing Sun Yat-Sen University Guangzhou 510275 China ObjectVideo Inc. Reston VA 20191-1410 United States

In this paper, we present an image parsing to text description (I2T) framework that generates text descriptions of image and video content based on image understanding. The proposed I2T framework follows three steps: 1) input images (or video frames) are decomposed into their constituent visual patterns by an image parsing engine, in a spirit similar to parsing sentences in natural language;2) the image parsing results are converted into semantic representation in the form of Web ontology language (OWL), which enables seamless integration with general knowledge bases;and 3) a text generation engine converts the results from previous steps into semantically meaningful, human readable, and query-able text reports. The centerpiece of the I2T framework is an andor graph (AoG) visual knowledge representation, which provides a graphical representation serving as prior knowledge for representing diverse visual patterns and provides topdown hypotheses during the image parsing. The AoG embodies vocabularies of visual elements including primitives, parts, objects, scenes as well as a stochastic image grammar that specifies syntactic relations (i.e., compositional) and semantic relations (e.g., categorical, spatial, temporal, and functional) between these visual elements. Therefore, the AoG is a unified model of both categorical and symbolic representations of visual knowledge. The proposed I2T framework has two objectives. First, we use semiautomatic method to parse images from the Internet in order to build an AoG for visual knowledge representation. Our goal is to make the parsing process more and more automatic using the learned AoG model. Second, we use automatic methods to parse image/video in specific domains and generate text reports that are useful for real-world applications. In the case studies at the end of this paper, we demonstrate two automatic I2T systems: a maritime and urban scene video surveillance system and a real-time automatic driving scene understanding

关键词： Syntactics

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