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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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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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Person re-identification across multi-camera system based on local descriptors

Person re-identification across multi-camera system based on...

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ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC

作者： Qiao Huang Jie Yang Yu Qiao Institute of Image Processing and Pattern Recognition and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

Tracking the same person across multiple cameras is an important task in multi-camera systems. It is also desirable to re-identify the individuals who have been previously seen with a single-camera. This paper addresses this problem by the re-identification of the same individual in two different datasets, which are both challenging situations from video surveillance system. In this paper, local descriptors are introduced for image description, and support vector machines are employed for high classification performance and so an efficient Bag of Features approach for image presentation. In this way, robustness against low resolution, occlusion and pose, viewpoint and illumination changes is achieved in a very fast way. We get promising results from the evaluation with situations where a number of individuals vary continuously from a multi-camera system.

关键词： Vocabulary Cameras Histograms Feature extraction Image color analysis Support vector machine classification Kernel

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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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第三届数字制造与自动化国际会议

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

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.

关键词： image processing production line billet character

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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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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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Online Transfer Boosting for object tracking

Online Transfer Boosting for object tracking

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International Conference on pattern recognition

作者： Changxin Gao Nong Sang Rui Huang Institute for Pattern Recognition and Artificial Intelligence Science and Technology on Multi-spectral Information Processing Laboratory Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781467322164

To deal with the drifting issue in visual tracking, we propose an Online Transfer Boosting (OTB) algorithm that transfers knowledge from three different source domains to the target domain to improve the performance of the online classifier used in tracking-by-detection. In particular, the OTB algorithm integrates three types of knowledge by: (1) transferring prior knowledge from the first frame using semi-supervised learning; (2) transferring appearance changes from the previous frames by dynamically updating the learning factor; and (3) transferring observed sample distribution knowledge from the current frame by reweighting the training samples. Experimental results on several public video sequences demonstrated promising performance of OTB in both tracking accuracy and stability.

关键词： Target tracking Boosting Visualization Video sequences Lighting Training Object tracking

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Target recognition method based on template matching in downward-looking infrared image

Target recognition method based on template matching in down...

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

作者： Zhu, Hu Deng, Lizhen Zhou, Gang Bai, Xiaodong Wang, Gaihua 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 Wuhan 430074 China College of Electrical and Electronic Engineering Huazhong University of Science and Technology 1037 Luoyu Road Wuhan 430074 China

ISBN: (纸本)9781467301718

Automatic ground target recognition technology in downward-looking infrared imagery is challenging problems due to the complexity of real-world. A robust ground target recognition method is proposed for downward-looking infrared (DLIR) image sequences in this paper. A complete model of the proposed method is designed firstly and the principles of some key technologies are introduced as following. Perspective transformation is used to solve the projective problems of landmark translation, rotation and scale variance in real-time image sequence. The size of landmark is estimated real-timely by using flight parameters and imaging parameters for getting the model with an appropriate scale. Based on the matching results of landmark and flight parameters, target position technology is proposed to identify the position of target by using the position relation between landmark and target. Experimental results using real-world image data with complicated background showed that the proposed method not only causes high precisely locating results, but also has good robustness for target occlusion. © 2012 IEEE.

关键词： Template matching

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Fast ground target detection method in infrared image sequences

Fast ground target detection method in infrared image sequen...

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

作者： Zhu, Hu Deng, Lizhen Wang, Gaihua Zhou, Gang Bai, Xiaodong 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 Wuhan 430074 China College of Electrical and Electronic Engineering Huazhong University of Science and Technology 1037 Luoyu Road Wuhan 430074 China

ISBN: (纸本)9781467301718

Automatic target detection (ATD) in infrared (IR) imagery is a fundamental and challenging task in computer vision. A fast automatic target detection method in IR image sequence is proposed in this paper. Since the position and scale of target change real-timely, we can predict the target position in real-time image by using the history position of target and flight parameters information of previous and current frames, and then estimate the scale of target depending on flight parameters and imaging parameters for getting the model with the appropriate scale. In order to make the template matching more robust for target rotation, the template matching method based on parametric template vector is used to recognize the position of target. The detection result is identified by using multiframe integration based on recognition information of history and currant frames. Some experimental results using real-world images with complicated background validate the effectiveness and robustness of the proposed method under rotation and scale variance condition. © 2012 IEEE.

关键词： Template matching

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One-Class SVM assisted accurate tracking

One-Class SVM assisted accurate tracking

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ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC

作者： Keren Fu Chen Gong Yu Qiao Jie Yang Irene Guy Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai China Chalmers tekniska hogskola Goteborg SE

Recently, tracking is regarded as a binary classification problem by discriminative tracking methods. However, such binary classification may not fully handle the outliers, which may cause drifting. In this paper, we argue that tracking may be regarded as one-class problem, which avoids gathering limited negative samples for background description. Inspired by the fact the positive feature space generated by One-Class SVM is bounded by a closed sphere, we propose a novel tracking method utilizing One-Class SVMs that adopt HOG and 2bit-BP as features, called One-Class SVM Tracker (OCST). Simultaneously an efficient initialization and online updating scheme is also proposed. Extensive experimental results prove that OCST outperforms some state-of-the-art discriminative tracking methods on providing accurate tracking and alleviating serious drifting.

关键词： Target tracking Support vector machines Training Feature extraction Face Boosting Semisupervised learning

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