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2012 International Conference on Image processing, Computer Vision, and pattern recognition, IPCV 2012

作者： Zhang, Tianxu Zhou, Gang Yang, Ying Weng, Wenjie Sun, Xiangdong Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology State Key Laboratory for Multispectral Information Processing Technologies Wuhan Hubei China

ISBN: (纸本)9781601322258

In actual imaging process, the projection or silhouette of a three-dimensional moving object is variable in shape, scale and resolution to make its recognizability also unstable. A remedy is suggested on concepts defined in this paper as the dynamic feature space of the pattern. The necessity of developing feature models of multi-scale characteristic view for three-dimensional moving airplane objects and the rationality of using a usual constraint on airplane object moving characteristics are discussed. Thus, a novel multi-scale intelligent recursive recognizing (MUSIRR) method for image sequences is proposed. An intelligent recognizer composed of hybrid neural networks and logic decision-making modules is constructed with the BP neural networks and RBF networks as the building blocks of the recognizer. The rationality and effectiveness of the new method proposed in this paper have been verified by results of massive simulation and actual experiments on several types of airplane object.

关键词： Decision making

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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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Integrating segmentation and classification accuracy for accuracy assessment in object-based image analysis

Integrating segmentation and classification accuracy for acc...

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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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Research on the digital system of archaeological

Research on the digital system of archaeological

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第四届国际遥感考古会议

作者： CAO Ligang WANG Xuben MIAO Fang YI Fasheng Key Laboratory of Earth Exploration & Information Techniques of Ministry of Education Director of Key Lab of Pattern Recognition & Intelligent Information Processing of Sichuan Province

The digital system of Archaeological includes multi-scale non-destructive detection of archaeological methods,data mining technologies and the GIS of archaeological *** preservation is not just for the protection of cultural relics has been *** non-destructive detection method to detect archaeological artifacts and clarify the situation of cultural relics buried *** detection data through the using of data mining algorithm make out the archaeological ***,use GIS technology to achieve the detection of data management and integration of data mining methods.A whole system of digital archaeological built on the GIS platform,based on the using of data mining technology to achieve a detection method and archaeological information mapping,the system for the digital archaeology has provided a complete technical support.

关键词： Archaeology explore GIS Data mining

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An improved method of identification based on thermal palm vein image 1

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19th International Conference on Neural information processing, ICONIP 2012

作者： Wang, Ran Wang, Guoyou Chen, Zhong Liu, Jianguo Shi, Yu National Key Laboratory of Science and Technology on Multi-spectral Information Processing Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology 1037 Luoyu Road Hongshan District 430074 Wuhan Hubei Province China

ISBN: (数字)9783642344817

ISBN: (纸本)9783642344800

Biological characteristics based on face, fingerprint and iris images have been extensively studied and used for the identification in the past few decades. As a new-born method, thermal palm vein pattern is gathering more and more attention all over the world. An improved method of identification based on thermal palm vein image is presented in the paper. Five steps are needed to have a person verified: 1) acquisition of infrared palm vein image;2) detection of ROI (region of interest);3) enhancement of the palm vein image;4) features extraction of the palm vein patterns;5) matching the features between the real palm vein and sample data. Experiments have been carried out on 178 different images and 176 images of them are correctly recognized with two in failure. Experiments show the detection rate is satisfied. © 2012 Springer-Verlag.

关键词： Image enhancement

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Discriminant analysis with Gabor phase for robust face recognition

Discriminant analysis with Gabor phase for robust face recog...

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2012 5th IAPR International Conference on Biometrics, ICB 2012

作者： Zhu, Jianfei Cao, Dong Liu, Sifei Lei, Zhen Li, Stan Z. Institute of Intelligent Information Processing Xidian University Xi'an China Hohai University No. 1 Xikang Road Nanjing Jiangsu Province China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences China China Research and Development Center for Internet of Thing China

ISBN: (纸本)9781467303941

This paper presents an occlusion robust image representation method and apply it to face recognition. Inspired from the recent work [15], we propose a Gabor phase difference representation for occlusion robust face recognition. Based on the good ability of Gabor filters to capture image structure and the robustness to image occlusion shown in this paper, Gabor phase features are expected to be discriminative and robust for face representation in occlusion case. Besides, we adopt spectral regression based discriminant analysis with the extracted Gabor phase features to find the most discriminant subspace to classify different faces. In this way, an occlusion robust face image discriminant subspace is derived. Extensive experiments with various occlusion cases show the efficacy of the proposed method. © 2012 IEEE.

关键词： Face recognition

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A novel and fast method for precise license plate location from digital images based on fusion of salient features

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2012年第19期6卷 511-519页

作者： Wang, Ran Wang, Guoyou Liu, Jianguo Chen, Zhong Shi, Yu Image Processing and Intelligent Key Laboratory of Ministry of Education of China Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 730074 China

The license plate location technique is an important image processing step in license plate recognition system. Vehicle license plates are distinguished from backgrounds using features proposed in existing literatures. However, the effect of location is quite affected by feature selection. In this paper, we propose a method of precise license plate location fusing salient features. The method is mainly divided into three steps. First, candidate license plate regions are detected using improved Harris corner feature with much less time than traditional method. Then, candidates are sifted to only retain license plates based on two salient features named color combination and mean difference which are first proposed in this paper. Finally, the license plates are located precisely according to the projection feature. In experiment, the proposed algorithm was tested with 1942 real images captured in different environment and the license plates are successfully located as 97.6% in average with only 109ms. The experiment results demonstrates the effectiveness and efficient of our algorithm.

关键词： Image processing

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Optimal stopping condition for iterative deconvolution method by the measurement of image texture

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2012年第15期6卷 109-119页

作者： Wang, Ze Yan, Luxin Jin, Mingzhi State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

The non-regularized iterative image restoration algorithms have been widely investigated in the literature. In this work, we focus on a common issue of non-regularized iterative methods, the stopping condition. A no-reference criterion of optimal stopping condition for non-regularized iterative deconvolution called Total Local Binary patterns (TLBP), which is based on the measurement of varying image texture during the deblurring procedure, is proposed. The metric utilizes the minimum of TLBP that is computed according to the LBP map of the blurred image to obtain the optimal restored image. We applied the Richardson-Lucy (RL) method to test the blurred version of the synthetic images and real images in experiments. Deconvolution experiments for Gaussian and out-offocus blur validate the effectiveness of the proposed method.

关键词： Image reconstruction

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Iterative data adaptive anisotropic image filtering

Iterative data adaptive anisotropic image filtering

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2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012

作者： Yang, Chang-Cai Zheng, Xin-Yi Tian, Jin-Wen Shang, Ke Tian, Xin Hao, Wei Institute for Pattern Recognition and Artificial Intelligence Science and Technology on Multi-Spectral Information Processing Laboratory Huazhong University of Science and Technology Wuhan 430074 China Electrical Engineering and Renewable Energy School China Three Gorges University Yichang 443002 China Institute of Intelligent Vision and Image Information College of Computer and Information Technology China Three Gorges University Yichang 443002 China

ISBN: (纸本)9781467314855

This paper presents a novel data-adaptive anisotropic filtering technique built on top of an iterative scheme. This new technique can preserve the original significant structures while suppressing noises to the largest extent. To achieve this goal, dominant orientation information of all gradients is used to control the local kernel adaptively. This results in elongated and elliptical contours spread along the directions of the local edge structure. With these locally adapted kernels, the smoothing is mostly effective along the edges, rather than across them. Therefore details in the original input can be preserved. The performance of the proposed data-adaptive anisotropic filter together with its iterative scheme are compared with the conventional Gaussian filter, anisotropic diffusion filter, the structure-adaptive anisotropic filter, and the iterative kernel regression scheme. The experimental results on both simulated Gaussian and Poission noisy images indicate that the proposed method performs the best, and the iterative scheme can significantly improve the performance of the noise suppressing while delivering high computation efficiency. © 2012 IEEE.

关键词： Iterative methods

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Adaptive iteration filter for suppression of impulse noise in color images

Adaptive iteration filter for suppression of impulse noise i...

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2012 International Conference on Mechatronic Systems and Automation Systems, MSAS 2012

作者： Wang, Gaihua Li, Dehua Zhao, Tongzhou Institute for pattern recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China The College of Physics and Information Science of Xinjiang Normal University Urumqi 830053 China Hubei Province Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan 430073 China

ISBN: (纸本)9783037854921

New impulse detection and filtering algorithm is proposed in color images. Based on fast peer group filter, the proposed filtering algorithm uses different iteration times to complete filter according to different impulse noise density. The extensive experimental results show that the proposed scheme provides better performance than many of the existing vector filters. Meanwhile, the proposed approach is simple and practical for real-time application. © (2012) Trans Tech Publications, Switzerland.

关键词： Impulse noise

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