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ICDAR2009 - 10th International Conference on Document Analysis and recognition

作者： Lettner, Martin Sablatnig, Robert Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Vienna University of Technology Austria

ISBN: (纸本)9780769537252

In this paper we propose a character segmentation method for multispectral images of ancient documents. Due to the low quality of the images the main idea of this study is to combine the multispectral behavior and contextual spatial information. Therefore we utilize a Markov Random Field model using the spectral information of the images and stroke properties to include spatial dependencies of the characters. Since the stroke properties and the Gaussian parameters for the imaging model are evaluated automatically the proposed segmentation method requires no training phase. We compared the method to state of the art character segmentation methods and demonstrate the effectiveness of combining spectral and spatial features for the segmentation of characters in multispectral images. © 2009 IEEE.

关键词： image segmentation

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Automated multi-camera surveillance for the prevention and investigation of bank robberies in Austria: A case study

Automated multi-camera surveillance for the prevention and i...

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3rd International Conference on Imaging for Crime Detection and Prevention, ICDP 2009

作者： Zambanini, S. Blauensteiner, P. Kampel, M. Pattern Recognition and Image Processing Group Vienna University of Technology Favoritenstr. 9/1832 1040 Vienna Austria

ISBN: (纸本)9781849192071

In this paper we present the recently granted tripleB-ID project that aims to detect suspicious actions and criminal offences in bank foyers. Based on the situation in Austria and on the actual needs of our partner bank, we deduce scenarios of interest and analyse the technical challenges. As a preliminary work, we furthermore present a fully automated method for the mapping between a static and a dynamic camera and show how this can be used to easily and fast set up a master-slave camera system.

关键词： Mapping

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Multispectral imaging for analyzing ancient manuscripts

Multispectral imaging for analyzing ancient manuscripts

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17th European Signal processing Conference, EUSIPCO 2009

作者： Lettner, Martin Sablatnig, Robert Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Vienna University of Technology 1040 Vienna Austria

In this paper we propose a method for segmenting characters in multispectral images of ancient documents. Due to the low quality of the document images the main idea of our study is to combine the multispectral behavior and contextual spatial information. Therefore we utilize a Markov Random Field model using the spectral information of the images and stroke properties to include spatial dependencies of the characters. The whole process is parameter free since we calculate the stroke properties and the Gaussian parameters for the imaging model automatically. The study shows the effectiveness of using multispectral data for a computer aided analysis of ancient text documents. We compare the results of the proposed segmentation method to traditional methods based on color images as well as gray level images. © EURASIP, 2009.

关键词： Computer aided analysis

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A novel method of aerial image classification based on attention-based local descriptors

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Procedia Earth and Planetary Science 2009年第1期1卷 1133-1139页

作者： Xu, Sheng Fang, Tao Huo, Hong Li, Deren Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200240 China The State Key Laboratory for Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan 430072 China

This paper proposes a novel method for object-based classification in very high spatial resolution aerial image. It combines the saliency maps very closely to extract the conspicuous local regions for better description of object and classification. Unlike the previous work on detection of the local regions, a biologically motivated selective attention model is presented in this paper, since not all the local regions are important for describing the objects. In order to model the attention region, we propose a new attention-based local descriptor using the saliency map and relative local features to reflect the region of interest (ROI). The experimental results on the VHR aerial image dataset show that the proposed approach can obtain the state-of-the-art classifica-tion performance. © 2009.

关键词： Object recognition image analysis image classification image segmentation Aerial images Bag of visual words Local descriptors Local feature Local region Novel methods Object based Region of interest Saliency map Selective attention model Very high spatial resolutions

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Weak metric learning for feature fusion towards perception-inspired object recognition

Weak metric learning for feature fusion towards perception-i...

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16th International Multimedia Modeling Conference on Advances in Multimedia Modeling, MMM 2010

作者： Li, Xiong Zhao, Xu Fu, Yun Liu, Yuncai Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China NY 14260 United States

ISBN: (纸本)3642113001

With extracted local features of a given image, computing its global feature under perceptual framework has shown promising performance in object recognition. However, under some tough applications with large intra-class variance, using only one kind of local feature is inadequate to build a robust classification system. To integrate the discriminability of complementary local features, in this paper, we extend the efficacy of perceptual framework to adapt to heterogeneous features. Given multiple raw global features, we propose a fusion strategy through metric learning, which is called weak metric learning in this work, for fusing high dimensional features. The fusion model is solved with the maximal kernel canonical correlation formulation with the multiple global features as outputs. Experimental results show that our method achieves significant improvements about 5% to 11% than the benchmark perceptual framework system, HMAX, on several difficult categories of object recognition with much less training samples and feature elements. © 2010 Springer-Verlag Berlin Heidelberg.

关键词： Object recognition

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Refining content based image retrieval via semi-supervised learning

Refining content based image retrieval via semi-supervised l...

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17th European Signal processing Conference, EUSIPCO 2009

作者： Zhu, Songhao Liu, Yuncai Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University 800 Dong Chuan Road 200240 Shanghai China

Content-based image retrieval plays a key role in the management of a large image database. However, the results of existing approaches are not as satisfactory for the gap between visual features and semantic concepts. Therefore, a novel scheme is here proposed. First, to tackle the problem of large computational cost involved in a large image database, a pre-filtering processing is utilized to filter out the most irrelevant images while keeping the most relevant ones. Second, the relevance between the query image and the remaining images is measured and the obtained relevance scores are stored for a later refinement processing. Finally, a semi-supervised learning algorithm is utilized to refine candidate ranking by taking into account both the pairwise information of unlabeled images and the relevance scores between the input query image and unlabeled images. Experiments conducted on a typical Corel dataset demonstrate the effectiveness of the proposed scheme. © EURASIP, 2009.

关键词： Learning algorithms

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A fast quantum mechanics based contour extraction algorithm

A fast quantum mechanics based contour extraction algorithm

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Medical Imaging 2009 - image processing

作者： Lan, Tian Sun, Yangguang Ding, Mingyue Institute for Pattern Recognition and Artificial Intelligence Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819475107

A fast algorithm was proposed to decrease the computational cost of the contour extraction approach based on quantum mechanics. The contour extraction approach based on quantum mechanics is a novel method proposed recently by us, which will be presented on the same conference by another paper of us titled "a statistical approach to contour extraction based on quantum mechanics". In our approach, contour extraction was modeled as the locus of a moving particle described by quantum mechanics, which is obtained by the most probable locus of the particle simulated in a large number of iterations. In quantum mechanics, the probability that a particle appears at a point is equivalent to the square amplitude of the wave function. Furthermore, the expression of the wave function can be derived from digital images, making the probability of the locus of a particle available. We employed the Markov Chain Monte Carlo (MCMC) method to estimate the square amplitude of the wave function. Finally, our fast quantum mechanics based contour extraction algorithm (referred as our fast algorithm hereafter) was evaluated by a number of different images including synthetic and medical images. It was demonstrated that our fast algorithm can achieve significant improvements in accuracy and robustness compared with the well-known state-of-the-art contour extraction techniques and dramatic reduction of time complexity compared to the statistical approach to contour extraction based on quantum mechanics. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Wave functions

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Recoverable image watermarking based on halftoning for content authentication

Recoverable image watermarking based on halftoning for conte...

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MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Wang, Zuxi Zhao, Xiangyuan Wang, Wenzong Hu, Hanping Li, Li Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan 430074 China

ISBN: (纸本)9780819478092

In this paper, a semi-fragile watermark solution based on quantization index modulation in the wavelet region was proposed. The algorithm employs a compressed halftoned binary image as watermark and embeds it in the wavelet domain through quantization index modulation, which can not only identify the authenticity of the content of digital image, but also recover the tampered image approximately. Because the watermark is a low-resolution original image, which carries the original image information, so the original image is not required when authenticating, and the tampered region can be recovered according to the watermark. The method can tolerate a certain degree of compression distortion or noise. Beside, a secret key is used to select the embedded watermark bits and their embedded positions to increase the security of watermarking. Experimental results show this semi-fragile watermarking algorithm is effective and practical for content authentication. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Binary images

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MRI brain tumor segmentation based on improved fuzzy c-means method

MRI brain tumor segmentation based on improved fuzzy c-means...

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Deng, Wankai Xiao, Wei Pan, Chao Liu, Jianguo Key Laboratory of Education Ministry for Image Processing and Intelligence Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan Hubei 430074 China

ISBN: (纸本)9780819478085

This paper focuses on the image segmentation, which is one of the key problems in medical image processing. A new medical image segmentation method is proposed based on fuzzy c- means algorithm and spatial information. Firstly, we classify the image into the region of interest and background using fuzzy c means algorithm. Then we use the information of the tissues' gradient and the intensity inhomogeneities of regions to improve the quality of segmentation. The sum of the mean variance in the region and the reciprocal of the mean gradient along the edge of the region are chosen as an objective function. The minimum of the sum is optimum result. The result shows that the clustering segmentation algorithm is effective. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Clustering algorithms

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RETRACTED ARTICLE: Digital fingerprinting based on synergetic

RETRACTED ARTICLE: Digital fingerprinting based on synergeti...

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2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009

作者： Wang, Zuxi Ge, Qiang Wang, Wenzong Hu, Hanping Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan China

ISBN: (纸本)9781424445073

Owing to the weaknesses of existing correlation detection methods in digital fingerprint matching, such as difficult to determine the threshold and low matching accuracy rate, a method proposed in digital fingerprint matching based on synergetic, which was applied in pattern recognition. Then, the experimental result indicated that the method proposed in the paper has a high matching rate. ©2009 IEEE.

关键词： Copyrights

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