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检索条件"机构=Pattern Recognition and Machine Intelligence Laboratory"

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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...

引用

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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Textured 3-D face reconstruction with two images in different views

Textured 3-D face reconstruction with two images in differen...

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Proceedings of the Biannual World Automation Congress

作者： Yuxing Mao He Wei Chunhua Feng Caixin Sun State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing China Centre for Pattern Recognition and Machine Intelligence (CENPARMI) Concordia University Montreal QUE Canada

In this paper, we present a new approach for textured 3-D face reconstruction based on two images in different views, which requires minimal user interaction by selecting eight pairs of feature points corresponding to each of the two images. These feature points have three functions: computing the fundamental matrix with the two face images based on epipolar geometry, estimating the poses of the images with respect to the pose of the frontal view, and determining the positions of the features for a rough adjustment of a generic 3-D face model. After the epipoles have been obtained, with the eight pairs of points as seeds, more matching points across the two images are detected under the constraints of epipolar lines. Then, the 3-D coordinates of the matching points can be computed with an SVD algorithm. After that, the generic 3-D model is adopted to optimize the constructed face model by eliminating the noise. Finally, the image closer to the frontal view is chosen as the texture map of our 3-D face model. Compared with some other previous works, there are fewer constraints to the poses of the images in our system and only one generic 3-D face model is needed. Experimental results demonstrate an encouraging performance of our method.

关键词： Image reconstruction Facial animation Humans Computational geometry Face detection Solid modeling Three dimensional displays Video sequences Sun Laboratories

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Pose Estimation Based on Two Images from Different Views

Pose Estimation Based on Two Images from Different Views

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IEEE Workshop on Applications of Computer Vision (WACV)

作者： Yuxing Mao Ching Y. Suen Caixin Sun Chunhua Feng The Key Laboratory of High Voltage Engineering & Electrical New Technology Ministry of Education Electrical Engineering College of Chongqing University Chongqing China Centre for Pattern Recognition and Machine Intelligence (CENPARMI) Concordia University Montreal QUE Canada

In this paper, we propose a new approach for face pose estimation based on two images from different views under certain conditions. Using a weak-perspective imaging model, six pose parameters were deduced, with four pairs of feature points properly chosen across the two face images. Through the scan-iteration algorithm, a robust performance was achieved, without solving non-linear equations. Comparing to some other methods which estimate rotation matrix based on fundamental matrix (F), our method focuses on the "absolute pose" with respect to front view rather than the "relative pose" between the two face images. "Absolute pose" is indispensable in most situations especially for 3D face modeling. Since our method does not depend on any 3D face models and frontal-view images, it can be applied not only to face recognition and 3D face modeling, but also to other relevant applications. Experimental results demonstrate the efficiency of our method

关键词： Face detection Head Video sequences Humans Robustness Face recognition Principal component analysis Feature extraction Application software pattern recognition

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A threshlod selection method based on multiscale and graylevel co-occurrence matrix analysis

A threshlod selection method based on multiscale and graylev...

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International Conference on Document Analysis and recognition

作者： Yun Li Mohamed Cheriet C.Y. Suen GM606 Center for Pattern Recognition and Machine Intelligence Concordia University Montreal QUE Canada Laboratory for Imagery Vision and Artificial Intelligence Ecole de Technologie Supérieure University of Quebec Montreal QUE Canada

Noise and complex backgrounds often make the thresholding of degraded document images difficult. In this paper, we propose a new threshold selection method to handle severely degraded document images. First, multiscale image description is adopted to analyze the image edge. From this, edge pixel pair information is derived and recorded by a graylevel co-occurrence matrix. An appropriate threshold value is chosen by measuring the edge pixel pair co-occurrence matrix. The new method is tested with degraded document images. The experimental results show it is resistant to noise and complex backgrounds.

关键词： Laplace equations Degradation Image analysis Image storage Text analysis Image edge detection pattern recognition machine intelligence Laboratories Artificial intelligence

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A threshlod selection method based on multiscale and graylevel co-occurrence matrix analysis

A threshlod selection method based on multiscale and graylev...

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8th International Conference on Document Analysis and recognition

作者： Li, Yun Cheriet, Mohamed Suen, Ching Y. Center for Pattern Recognition and Machine Intelligence Concordia University GM606 1455 de Maisonneuve Blvd. West Montreal Que. H3G 1M8 Canada Laboratory for Imagery Vision and Artificial Intelligence Ecole de Technologie Supérieure University of Quebec 1100 Notre-Dame West Montreal Que. H3C 1K3 Canada

ISBN: (纸本)0769524206

Noises and complex backgrounds often make the thresholding of degraded document images a difficult job. In this paper, we propose a new threshold selection method to handle severely degraded document images. First, multiscale image description is adopted to analyze the image edge. From it, edge pixel pair information is derived and recorded by a graylevel co-occurrence matrix. An appropriate threshold value is chosen by measuring the edge pixel pair co-occurrence matrix. The new method is tested with degraded document images. The experimental results show it is resistant to noises and complex backgrounds. © 2005 IEEE.

关键词： Threshold elements

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A segmentation method for touching italic characters

A segmentation method for touching italic characters

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International Conference on pattern recognition

作者： Yun Li S. Naoi M. Cheriet C.Y. Suen Center of Pattern Recognition and Machine Intelligence Concordia University Montreal QUE Canada Document Processing Laboratory Fujitsu Laboratories Limited Kawasaki Japan Laboratory for Imagery Vision and Artificial Intelligence Ecole de Technologie Supérieure University of Quebec Montreal QUE Canada

ISBN: (纸本)0769521282

Segmentation is an essential part of a recognition system. It is difficult to handle touching characters, especially for italic fonts. We present a method to achieve the accurate segmentation of touching italic characters. It is free of slant correction, so extra noises will not be introduced. We use slant projection and contour analysis to find the segmentation points. Then the shortest path approach is adopted for accurately locating the cut path of each candidate segmentation point. Based on dynamic programming, we can find the best segmentation result from those cut paths. By this method, we can improve the recognition rate on italic fonts.

关键词： Image segmentation Histograms pattern recognition Image recognition Dynamic programming Character recognition machine intelligence Laboratories Artificial intelligence Optical character recognition software

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Automatic filter selection using image quality assessment 7

Automatic filter selection using image quality assessment

引用

7th International Conference on Document Analysis and recognition, ICDAR 2003

作者： Souza, Andrea Cheriet, Mohamed Naoi, Satoshi Suen, Ching Y. Centre for Pattern Recognition and Machine Intelligence Concordia University 1455 de Maisonneuve Blvd. West Suite GM606 MontréalQXH3G 1M8 Canada Laboratory for Imagery ÉCole de Technologie Supérieure University of Québec 1100 Notre-Dame West MontréalQCH3C 1K3 Canada Document Processing Lab Fujitsu Labs Ltd. Kawasaki211-8588 Japan

ISBN: (纸本)0769519601

We present a method for automatically selecting the best filter to treat poor quality printed documents using image quality assessment. We introduce five quality measures to obtain information about the quality of the images, and morphological filters to improve their quality. A training set of 370 images was used to develop the system. Experimental results on the test set show a significant improvement in the recognition rate from 73.24% using no filter at all to 93.09% after applying a filter that was automatically selected. © 2003 IEEE.

关键词： Image quality

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Observer-dependent sharpening

Observer-dependent sharpening

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IEEE International Conference on Image Processing

作者： H.R. Tizhoosh Pattern Recognition and Machine Intelligence Laboratory Systems Design Engineering University of Waterloo Waterloo ONT Canada

Image quality evaluation by human observers is heavily subjective in nature. Individual observers judge the image quality differently. In previous works, an observer-dependent system for subjective image enhancement, which is based on fusion of different algorithms, was introduced. In this paper, the system configuration for sharpness/smoothness is discussed and experimental results are provided.

关键词： Image enhancement Image quality Humans pattern recognition machine intelligence Design engineering Systems engineering and theory Image processing Man machine systems Convolution

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Fast two-level Viterbi search algorithm for unconstrained handwriting recognition

Fast two-level Viterbi search algorithm for unconstrained ha...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Alessandro L. Koerich Robert Sabourin Ching Y. Suen Laboratory d'Imagerie de Vision et d'Intelligence Artificielle Ecole de Technologie Supérieure Montreal Canada Centre for Pattern Recognition and Machine Intelligence Concordia University Montreal Canada

This paper describes a fast two-level Viterbi search algorithm for recognizing handwritten words as a sequence of characters concatenated according to a lexicon. The algorithm is based on hidden Markov model (HMM) representations of characters and it breaks up the computation of word likelihood scores into two levels: state level and character level. This enables the reuse of likelihood scores of characters to decode all words in the lexicon, avoiding repeated computation of state sequences. Experimental results with an 85,000-word vocabulary indicate that the computational cost of an off-line handwritten word recognition system may be reduced by more than a factor of 20 while not introducing search errors.

关键词： Handwriting recognition

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A hybrid large vocabulary handwritten word recognition system using neural networks with hidden Markov models

A hybrid large vocabulary handwritten word recognition syste...

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International Workshop on Frontiers in Handwriting recognition

作者： A.L. Koerich Y. Leydier R. Sabourin C.Y. Suen Laboratory dE28099Imagerie de Vision et dE28099Intelligence Artificielle Ècole de Technologie Supérieure Montreal Canada Laboratory Reconnaissance de Formes et Vision I.N.S.A. Villeurbanne France Centre for Pattern Recognition and Machine Intelligence Concordia University Montreal Canada

We present a hybrid recognition system that integrates hidden Markov models (HMM) with neural networks (NN) in a probabilistic framework. The input data is processed first by a lexicon-driven word recognizer based on HMMs to generate a list of the candidate N-best-scoring word hypotheses as well as the segmentation of such word hypotheses into characters. An NN classifier is used to generate a score for each segmented character and in the end, the scores from the HMM and the NN classifiers are combined to optimize performance. Experimental results show that for an 80,000-word vocabulary, the hybrid HMM/NN system improves by about 10% the word recognition rate over the HMM system alone.

关键词： Vocabulary Handwriting recognition Neural networks Hidden Markov models pattern recognition Character recognition Character generation Image segmentation Viterbi algorithm Reconnaissance

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