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Automatic Identification of Oriental and Other Scripts in Image Documents

International Journal of Computer Processing of Languages 2005年第2期18卷 77-94页

作者： C. Y. SUEN S. BERGLER N. NOBILE W. PAN B. WAKED Centre for Pattern Recognition and Machine Intelligence CENPARMI Concordia University 1455 de Maisonneuve Blvd. West Suite GM-606 Montreal Quebec H3G 1M8 Canada

Increasing amount of paper documents are produced and received by many organizations. Frequently, they have to be digitized for electronic archiving and later information retrieval or data mining, requiring scanning and OCR. Since OCR techniques are language dependent, the language of the original document must be identified first by advanced technology. This paper describes two methods of identifying Oriental languages among four language groups, i.e. Oriental, Roman, Cyrillic, and Arabic. One method is based on features extracted from the shapes of words and letters, while the other is based on global analysis of text pieces using Gabor filters. Experimental results on hundreds of both clean and noisy documents indicate that the proposed classification approaches look quite promising. The use of linguistic analysis to enhance the results is also discussed.

关键词： OCR Script Arabic Oriental Roman Cyrillic Gabor filters

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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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Automatic segmentation and recognition system for handwritten dates on canadian bank cheques 7

Automatic segmentation and recognition system for handwritte...

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

作者： Xu, Qizhi Lam, Louisa Suen, Ching Y. Centre for Pattern Recognition and Machine Intelligence Concordia University 1455 de Maisonneuve Boul. West Suite GM 606 MontrealQCH3G 1M8 Canada Department of Mathematics Hong Kong Institute of Education 10 Lo Ping Road Tai Po Hong Kong

ISBN: (纸本)0769519601

This paper describes a system being developed to recognize date information handwritten on Canadian bank cheques. A segmentation based strategy is adopted in this system. In order to achieve high performances in terms of efficiency and reliability, a knowledge-based module is proposed for the date segmentation and a cursive month word recognition module is implemented based on a combination of classifiers. The interaction between the segmentation and recognition stages is properly established by using multihypotheses generation and evaluation modules. As a result, promising performance is obtained on a test set from a reallife standard cheque database. © 2003 IEEE.

关键词： Knowledge based systems

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A low-cost parallel K-means VQ algorithm using cluster computing 7

A low-cost parallel K-means VQ algorithm using cluster compu...

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

作者： Britto, Alceu De S. De Souza, Paulo S.L. Sabourin, Robert De Souza, Simone R.S. Borges, Díbio L. 80215-901 Brazil 84100-000 Brazil ÉCole de Technologie Supérieure 1100 Rue Notre Dame Ouest MontrealQCH3C1K3 Canada Centre for Pattern Recognition and Machine Intelligence 1455 de Maisonneuve Blvd. West Suite GM 606 MontrealQCH3G 1M8 Canada

ISBN: (纸本)0769519601

In this paper we propose a parallel approach for the Kmeans Vector Quantization (VQ) algorithm used in a twostage Hidden Markov Model (HMM)-based system for recognizing handwritten numeral strings. With this parallel algorithm, based on the master/slave paradigm, we overcome two drawbacks of the sequential version: A) the time taken to create the codebook;and b) the amount of memory necessary to work with large training databases. Distributing the training samples over the slaves' local disks reduces the overhead associated with the communication process. In addition, models predicting computation and communication time have been developed. These models are useful to predict the optimal number of slaves taking into account the number of training samples and codebook size. © 2003 IEEE.

关键词： Cluster computing

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Automatic filter selection using image quality assessment 7

Automatic filter selection using image quality assessment

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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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A generic method of cleaning and enhancing handwritten data from business forms

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International Journal on Document Analysis and recognition 2001年第2期4卷 84-96页

作者： Ye, Xiangyun Cheriet, Mohamed Suen, Ching Y. Centre for Pattern Recognition and Machine Intelligence Concordia University Suite GM606 1455 de Maisonneuve Blvd. West Montréal QC H3G 1M8 Canada Laboratory for Imagery Vision and Artificial Intelligence École de Technologie Supérieure University of Quebec 1100 rue Notre-Dame Ouest Montréal QC H3C 1K3 Canada

The automation of business form processing is attracting intensive research interests due to its wide application and its reduction of the heavy workload due to manual processing. Preparing clean and clear images for the recognition engines is often taken for granted as a trivial task that requires little attention. In reality, handwritten data usually touch or cross the preprinted form frames and texts, creating tremendous problems for the recognition engines. In this paper, we contribute answers to two questions: "Why do we need cleaning and enhancement procedures in form processing systems?" and "How can we clean and enhance the hand-filled items with easy implementation and high processing speed?" Here, we propose a generic system including only cleaning and enhancing phases. In the cleaning phase, the system registers a template to the input form by aligning corresponding landmarks. A unified morphological scheme is proposed to remove the form frames and restore the broken handwriting from gray or binary images. When the handwriting is found touching or crossing preprinted texts, morphological operations based on statistical features are used to clean it. In applications where a black-and-white scanning mode is adopted, handwriting may contain broken or hollow strokes due to improper thresholding parameters. Therefore, we have designed a module to enhance the image quality based on morphological operations. Subjective and objective evaluations have been studied to show the effectiveness of the proposed procedures. © 2001 Springer-Verlag Berlin Heidelberg.

关键词： Binary images

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Segmentation of date field on Bank cheques

Segmentation of date field on Bank cheques

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International Association of pattern recognition, IAPR 2000 held jointly with 8th International Workshop on Structural and Syntactic pattern recognition, SSPR 2000 and 3rd International Workshop on Statistical Techniques in pattern recognition, SPR 2000

作者： Lam, Louisa Fan, Rong Xu, Qizhi Suen, Ching Y. Centre for Pattern Recognition and Machine Intelligence Concordia University 1455 de Maisonneuve Blvd. Suite GM-606 West MontréalQCH3G 1M8 Canada Department of Mathematics Hong Kong Institute of Education 10 Lo Ping Road Tai Po Hong Kong

ISBN: (纸本)3540679464

This article describes a system being developed to segment handwritten date fields on bank cheque images. The handwritten information extracted from the date zone is segmented into day, month and year, and a hypothesis is also made on the writing style of the month (in word or digits). The system has been implemented and tested on cheque images. Subsequent modifications have also been designed and implemented to include contextual information in the determination of segmentation points. Results have shown that the system is effective;with continuing improvements, the system is expected to be a useful component for processing the date written on cheques. © Springer-Verlag Berlin Heidelberg 2000.

关键词： Image segmentation

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recognition of English and Arabic numerals using a dynamic number of hidden neurons 5

Recognition of English and Arabic numerals using a dynamic n...

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5th International Conference on Document Analysis and recognition, ICDAR 1999

作者： Said, Fady N. Yacoub, Rita A. Suen, Ching Y. Center for Pattern Recognition and Machine Intelligence Concordia University Suite GM606 1455 De Maisonneuve Blvd. West MontréalQCH3G 1M8 Canada

ISBN: (纸本)0769503187

The paper introduces a method of finding the neighborhood of the optimal number of hidden neurons for an error backpropagation neural network with a single hidden layer. It is based on a study of the curvature of the error function, during the training phase of the network. The method assures convergence and bypasses local minimas. Experimental results show the uniqueness of the method's solution regardless of the initial values of the network's parameters. Two neural networks were built, one for recognizing unconstrained handwritten English numerals and the other for Arabic numerals. recognition results and comparison with other methods are also presented. © 1999 IEEE.

关键词： Character recognition

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Sorting and recognizing cheques and financial documents 3rd

Sorting and recognizing cheques and financial documents

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3rd IAPR Workshop on Document Analysis Systems, DAS 1998

作者： Suen, Ching Y. Liu, Ke Strathy, Nick W. Centre for Pattern Recognition and Machine Intelligence Concordia University Suite GM-606 1455 de Maisonneuve Blvd West MontrealQCH3G 1M8 Canada

ISBN: (纸本)3540665072

In collaboration with financial institutions and utility companies, we have carried out substantial research on document analysis and handwriting recognition. This paper describes our prototype which can differentiate between cheques and remittance slips, between English and French cheques, and recognize their contents. A new technique of sorting handwritten cheques and financial documents will be described. It is based on the detection of the structural properties printed on such documents. Handwritten numeric amounts are recognized by a multiple-expert system. These systems have been applied to read handwritten cheques and numerous financial documents with a great variety of backgrounds, colours, and designs in real-life environments. Their performance will be presented and analyzed. © Springer-Verlag Berlin Heidelberg 1999.

关键词： Expert systems

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