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2012 3rd IEEE/IET International Conference on Audio, Language and image processing, ICALIP 2012

作者： Li, Nan Huo, Hong Fang, Tao Institute of Image Processing and Pattern Recognition Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China

ISBN: (纸本)9781467301718

An accuracy assessment method that integrates segmentation and classification accuracy is proposed to meet the requirements of object-based image analysis. Segmentation errors are measured by establishing the relationship between pixels and their corresponding segments according to the overlaps of segments and reference polygons. Then, two improved confusion matrices that take the segmentation errors into consideration are used: one for pixel-level classification results, and the other for object-level classification results. A final accuracy assessment combines the statistics of these two confusion matrices. The proposed method can be applied to segmentation scale selection in the hierarchical interpretation system. An experiment on a SPOT5 image demonstrates the effectiveness of this method for segmentation scale selection, which can guide the fusion of objects of different scales to obtain a higher accuracy. © 2012 IEEE.

关键词： image analysis

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Accurate object tracking based on homography matrix

Accurate object tracking based on homography matrix

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2012 International Conference on Computer Science and Service System, CSSS 2012

作者： Zhang, Miaohui Hou, Yandong Hu, Zhentao Institute of Image Processing and Pattern Recognition Shanghai JiaoTong University Shanghai 200240 China School of Computer and Information Engineering Henan University Kaifeng 475004 China

ISBN: (纸本)9780769547190

We present a novel object tracking framework that can efficiently track such 2-D affine motions of the object image. A coarse-to-fine tracking strategy is explored in the tracking framework. Firstly, the object image region is selected from the first frame, the scale-invariant feature (SIFT) extracted from the object image region is utilized as the object model. Secondly, the highest likelihood object region is preliminarily located by the particle filter (PF) algorithm in the following video frame, and the SIFT feature points are also extracted from the highest likelihood object region, matching point set between object model and the highest likelihood region is attained by the scale-invariant feature transform, then the corresponding homography matrix is robustly estimated through the random sample consensus (RANSAC) algorithm. Finally, the affine parameters which determine the location and pose of the object are obtained. Simulation results demonstrate the efficiency of our approach. © 2012 IEEE.

关键词： Tracking (position)

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Maneuvering target tracking algorithm based on multiple model Rao-Blackwellised particle filter

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Journal of Information and Computational Science 2012年第7期9卷 1941-1948页

作者： Hu, Zhentao Jin, Yong Li, Jie Liu, Xianxing Institute of Image Processing and Pattern Recognition Henan University Kaifeng 475004 China

Target tracking is highly nonlinear problem that has been successfully addressed in recent years using particle filtering method. However, the realization of particle filter has a large amount of calculation. In order to improve the computational complexity caused by the augment of model in maneuvering tracking system, Rao-Blackwellised particle filter with better real-time and filtering precision relative to the standard particle filter, is introduced into multiple model particle filter framework. And a novel multiple model Rao-Blackwellised particle filter is proposed in this paper. Due to the dynamic combination of above two algorithms, the real-time and reliability is effective improved. The theoretical analysis and experimental results show the efficiency of the proposed algorithm. 1548-7741/Copyright © 2012 Binary Information Press.

关键词： Target tracking

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Adaptive multi-feature tracking in particle swarm optimization based particle filter framework

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Journal of Systems Engineering and Electronics 2012年第5期23卷 775-783页

作者： Miaohui Zhang Ming Xin Jie Yang Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 P. R. China Institute of Image Processing and Pattern Recognition Henan University Kaifeng 475001 P. R. China

This paper proposes a particle swarm optimization（PSO） based particle filter（PF） tracking framework,the embedded PSO makes particles move toward the high likelihood area to find the optimal position in the state transition stage,and simultaneously incorporates the newest observations into the proposal distribution in the update *** the proposed approach,likelihood measure functions involving multiple features are presented to enhance the performance of model ***,the multi-feature weights are self-adaptively adjusted by a PSO algorithm throughout the tracking *** are three main ***,the PSO algorithm is fused into the PF framework,which can efficiently alleviate the particles degeneracy ***,an effective convergence criterion for the PSO algorithm is explored,which can avoid particles getting stuck in local minima and maintain a greater particle ***,a multi-feature weight self-adjusting strategy is proposed,which can significantly improve the tracking robustness and *** performed on several challenging public video sequences demonstrate that the proposed tracking approach achieves a considerable performance.

关键词： particle filter particle swarm optimization adaptive weight adjustment visual tracking

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A REVIEW ON ARTERY WALL SEGMENTATION TECHNIQUES AND INTIMA-MEDIA THICKNESS MEASUREMENT FOR CAROTID ULTRASOUND imageS

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Journal of Innovative Optical Health Sciences 2012年第1期5卷 75-84页

作者： XIN YANG WANJI HE KAITONG LI JIAOYING JIN XUMING ZHANG MING YUCHI MINGYUE DING State Key Laboratory for Multi-Spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence(IPRAI)Huazhong University of Science and Technology Wuhan 430074HubeiChina Image Processing and Intelligence Control Key Laboratory of Education Ministry of China School of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074HubeiChina

Stroke and heart attack,which could be led by a kind of cerebrovascular and cardiovascular disease named as atherosclerosis,would seriously cause human morbidity and *** is important for the early stage diagnosis and monitoring medical intervention of the *** stenosis is a classical atherosclerotic lesion with vessel wall narrowing down and accumulating plaques *** carotid artery of intima-media thickness(IMT)is a key indicator to the *** the development of computer assisted diagnosis technology,the imaging techniques,segmentation algorithms,measurement methods,and evaluation tools have made considerable *** imaging,being real-time,economic,reliable,and safe,now seems to become a standard in vascular assessment methodology especially for the measurement of *** review firstly attempts to discuss the clinical relevance of measurements in clinical practice at first,and then followed by the challenges that one has to face when approaching the segmentation of ultrasound ***,the commonly used methods for the IMT segmentation and measurement are ***,discussion and evaluation of different segmentation techniques are *** overview of summary and future perspectives is given finally.

关键词： Ultrasound(US)images carotid artery intima-media thickness(IMT) atherosclerosis image segmentation computer assisted diagnosis(CAD)

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Detection of billet character in complex production line scene

Detection of billet character in complex production line sce...

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2012 3rd International Conference on Digital Manufacturing and Automation, ICDMA 2012

作者： Hong, Hanyu Yu, Zhejun Zhang, Xiuhua Laboratory for Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan 430205 China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780769547725

Character information is hard to detect in billet scene images by CCD camera. In this paper, we present a method for detection of billet characters from measurements of recursive segmented image. This recursive segmented method can be used in a wide variety of billet scenes. According to high temperature and complex scene in the rolling line, we use an effective clustering and projection characteristics to determine the terminal condition of recursive segmentation. Then we can label character candidate regions in turn by this effective characteristics, and select the regions we want to achieve. The experiments show that this method makes full use of the characteristics of region and clustering. It can improve the quality of detection, and the detection result meets the need of practical application. © 2012 IEEE.

关键词： CCD cameras

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A key management mechanism for DHT networks

A key management mechanism for DHT networks

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2012 8th International Conference on Intelligent Information Hiding and Multimedia Signal processing, IIH-MSP 2012

作者： Zhang, Wen Niu, Shao-Zhang Zou, Jian-Cheng School of Computer Science Beijing University of Posts and Telecommunications Beijing 100876 China Institute of Image Processing and Pattern Recognition North China University of Technology Beijing 100144 China

ISBN: (纸本)9780769547121

This paper proposes a key management mechanism by DH distributed key tree for the DHT network, which is based on the DHT network routing mechanism and network topology structure. The scheme uses the DH algorithm for key agreement, to ensure that the nodes in the DHT network are able to maintain a limited number of keys, and on this basis to complete encryption of routing messages across the network. The key management mechanism provides a secure shared key for the data encryption between the nodes in the DHT network, and maintains a high degree of consistency with the DHT network topology structure, and it has broad application prospects. © 2012 IEEE.

关键词： Network routing

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Robust object tracking by combining boosting learning and particle filter

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Journal of Computational Information Systems 2012年第22期8卷 9593-9601页

作者： Li, Tianyu Liu, Jia Gong, Chen Yang, Jie Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200240 China

Online adaptive object tracking has been studied for years. These methods focus on dealing with the significant variation of object's appearance. However, over updating of the tracker may result in drifting problem, especially when the object is occluded by a similar object. In this paper, we present a method of object tracking within a hybrid feature framework which efficiently alleviates the drifting problem. Our framework consists of a particle filter tracker and an Adaboost classifier. The particle filter is used to offer a preliminary target area by HSV histogram feature. Then the Adaboost classifier provides more accurate target information in this area by Haar-like feature. With the combination of two different feature models, our approach is able to update the tracker precisely. Experimental results demonstrate that our algorithm can robustly track the target object. Copyright © 2012 Binary Information Press.

关键词： Bandpass filters

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Bidirectional two-dimensional algorithm based on Divisor method

Bidirectional two-dimensional algorithm based on Divisor met...

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IEEE International Conference on Signal processing, Communications and Computing (ICSPCC)

作者： Peiyan Jia Haishun Du Yong Jin Zhang Fan Institute of Image Processing and Pattern Recognition Henan University Kaifeng China

In recent years, the subspace learning methods based on the bidirectional two-dimensional are widely used in extracting features of face image. However, the existing bidirectional two-dimensional subspace learning methods always assume that the numbers of two mapping matrices' projection vectors are equal. Although this can simplify the computation, it will possibly cause the following two questions: (1) Get rid of information with classification properties; (2) Reserve information without classification properties. In order to solve the problem, this paper proposes a method called Divisor method and use it in bidirectional two-dimensional subspace learning method. This method calculates the percentage loss of mapping matrix in both row and column directions firstly, and then use the Divisor method to select the numbers of two mapping matrices' projection vectors, which base on the principle of minimum total percentage loss. The experimental results on ORL and YALE face database show that the proposed method yields greater recognition accuracy while reduces the overall computational complexity.

关键词： Databases Training Covariance matrix Principal component analysis Accuracy Face Vectors

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Spatiotemporal saliency based on distributed opponent oriented energy

Spatiotemporal saliency based on distributed opponent orient...

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International Conference on pattern recognition

作者： Yue Zhou Kun Shi Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University China

ISBN: (纸本)9781467322164

A computational saliency model utilizing bio-inspired features for spatiotemporal saliency is presented in this paper. We first propose distributed opponent oriented energy for compact local dynamic texture description motivated by Human Vision System. Then, we integrate the derived motion characterization and a revised self-resemblance saliency framework. High effectiveness and efficiency of the proposed method is extensively demonstrated both qualitatively and quantitatively, for background subtraction in the cases of extremely dynamic scenes and camera jitter. In terms of the trade-off between accuracy and computation cost, our method achieves competitive results in contrast to the state-of-art algorithm.

关键词： Spatiotemporal phenomena Dynamics Computational modeling Heuristic algorithms pattern recognition Biological system modeling Cameras

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