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Building a perception based model for reading cursive script 3

Building a perception based model for reading cursive script

引用

3rd international conference on Document Analysis and recognition, ICDAR 1995

作者： Cote, M. Lecolinet, E. Cheriet, M. Suen, C.Y. Telecom Paris Departement Signal 46 rue Barrault Paris Cedex 1375634 France E.T.S Universite du Quebec 4750 Avenue Henri-Julien MontrealQCH2T2C8 Canada CENPARMI Concordia University 1455 de Maisonneuve West MontrealQC3G1M8 Canada

ISBN: (纸本)0818671289

This paper presents a new perception based model for reading cursive script. We describe the organization of our pseudo-neuronal system and show the role of activation mechanism in perceiving and reading cursive script. We have introduced into our model some characteristics specific to cursive script. First, we use more appropriate features such as ascenders and descenders. Second, we deal with the ambiguity of letter location by introducing the concept of the fuzzy position. The location as well as the missing letters are deduced from the context (i.e. the word-letter lexicon). After implementation of our method, preliminary qualitative results have been obtained and are discussed. We are concentrating now on further formalizing and generalizing the proposed model on a larger data base. © 1995 IEEE.

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Extracting meaningful handwriting features with fuzzy aggregation method

Extracting meaningful handwriting features with fuzzy aggreg...

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international conference on Document Analysis and recognition

作者： A. Malaviya L. Peters GMD-German National Research Center of Information Technology Saint Augustine USA

recognition methods use different features to assign a pattern to a prototype class. The recognition accuracy strongly depends on the selected features. We present a novel fuzzy methodology to extract appropriate fuzzy features from the handwriting data. From these meaningful features a set of linguistic rules are derived which in turn constitute a fuzzy rule base for character recognition. The fuzzy features are confined to their meaningfulness with the help of a multistage feature aggregation scheme.

关键词： Feature extraction data mining Handwriting recognition Prototypes Fuzzy sets Character recognition Humans pattern recognition Writing Shape

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Adaptive hierarchical indexing and constrained localization: Matching characteristic views 3rd

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3rd international Computer Science conference (ICSC 95) - Image Analysis Applications and Computer Graphics

作者： Bellaire, G Lubbe, M Computer Vision Group Dep. of Computer Science Technical University of Berlin Franklinstr. 28-29 FR 3-11 Berlin 10587 Germany

ISBN: (纸本)3540606971

This article presents a complete hybrid object recognition system for three-dimensional objects using the characteristic view (ChV) idea. To apply the ChV representation method in a recognition system investigations are needed concerning the processing of large object data bases. First we present two methods to reduce the number of views in the object data base. Second we developed an accumulator (AC)-based matching strategy combined with a localization process. This strategy bases on a hierarchical indexing structure that uses a Gaussian distributed voting. The off-line part of the matching includes a statistical analysis of the object data base and an interface to process results of a sensor configuration analysis. The calculated results support the construction of an adapted layer model suitable for hierarchical indexing. Further an unsupervised learning module is introduced;that investigates the measurement errors and adapts the system online. Results of the matching are verified by a localization tool, which uses an interpretation tree search combined by a shape from angle method and a constrained alignment technique. The article shows results with real greyscale images.

关键词： Object recognition

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A new modeling method for on-line handwriting recognition

A new modeling method for on-line handwriting recognition

引用

international conference on Document Analysis and recognition

作者： G. Menier G. Lorette P. Gentric IRISA Rennes France Laboratoires d''Electronique Philips Limeil-Brevannes France

This paper introduces and discusses the concept of stable and shared information and its application in a new modeling method based on the selection of features. The model constructed is used for the automatic detection of scriptor-independent information. The selected features are treated as functions in order to allow a continuous interpretation of the script signal. This proposed representation permits the joint interpretation of on-line and off-line information. The paper then goes on to present some experimental results.

关键词： Handwriting recognition data mining Feature extraction Character recognition pattern recognition pattern analysis Keyboards Mice Information analysis Graphics

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pattern recognition and beautification for a pen based interface

Pattern recognition and beautification for a pen based inter...

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international conference on Document Analysis and recognition

作者： L. Julia C. Faure ENST Department SIG CNRS URA 820 Paris France

The paper presents the algorithms for recognition and beautification which are used in incremental graphic design applications. These applications propose multimodal interfaces integrating handwriting, gesture, and speech on a pen-computer. User and computer collaborate to perform the task of incrementally designing a drawing. Processing and data representation take into account the variable quality of handwritten data, the man-machine interaction context and the cooperation between the user and the interpretation system. Both recognition algorithms may be used in combination in order to increase the speed and the set of recognized figures. Local recognition is followed by the beautification of the global structure in order to detect alignments and logical structures. The beautification enables the user to display a clean version of the original draft. The applications which the authors developed are used to recognize tables, gestures, geometrical figures or diagram networks.

关键词： pattern recognition Application software Man machine systems Computer graphics Algorithm design and analysis Collaboration Computer displays Feedback Speech recognition Testing

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A formal model for document processing of business forms

A formal model for document processing of business forms

引用

international conference on Document Analysis and recognition

作者： M. Cheriet J.N. Said C.Y. Suen Laboratoire dImagerie deVision et dIntelligence ArtificielleEcole de Technologie Superieure Universite du Quebec Montreal QUE Canada Center for Pattern Recognition and Machine Intelligence Concordia University West Montreal QUE Canada

We present a formal model for processing gray-scale images of business forms such as bank cheques. The formal model is based on a new hybrid-based approach namely the base lines. In fact, to segment handwritten and hand-printed data from bank cheques, knowledge rules and base lines will have important roles to segment and extract the information from bank cheques. The architectural design as well as the major components of the system is discussed in full detail. Moreover, the significant use of the morphological followed by the topological processing on gray-scale images is used as a major aspect to restore the lost information after the elimination of the background and the base lines from the gray-scale cheques.

关键词： Image segmentation Gray-scale data mining Pixel Image restoration Information filtering Information filters Object detection Image enhancement Surface-mount technology

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A feature point clustering approach to the segmentation of form documents

A feature point clustering approach to the segmentation of f...

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international conference on Document Analysis and recognition

作者： Kuo-Chin Fan Jeng-Ming Lu Jing-Yuh Wang Institute of Computer Science and Information Engineering National Central University Chungli Taiwan

ISBN: (纸本)0818671289

Among various kinds of documents, forms are one of the important types. The prerequisite for form optical character recognition (Form OCR) is the extraction of characters from form documents. The authors present a clustering based technique for extracting characters from form documents. In this method, they treat the character extraction process as a pattern clustering problem. The feasibility of the novel method is demonstrated through experimenting various kinds of forms. Experimental results reveal the feasibility of the novel method.

关键词： Character recognition Feature extraction Optical character recognition software data mining Image segmentation Clustering algorithms pattern clustering Image storage Optical devices Storage automation

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The evaluation of feature extraction criteria applied to neural network classifiers

The evaluation of feature extraction criteria applied to neu...

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international conference on Document Analysis and recognition

作者： W. Utschick P. Nachbar C. Knobloch A. Schuler J.A. Nossek Institute of Network Theory and Circuit Design Technical University Munich Munich Germany

Feature extraction is a crucial part of classification procedures. In this paper we present an approach to utilize feature extraction criteria to predict the potential efficiency of a neural network classifier. Statistical and geometrical criteria are introduced for analysis. The complete system of our research consists of a class of generalized Hough-transformations for feature extraction and a subsequent neural network. The neural network performs the classification based on respective features. For an example we concentrated on a pattern recognition problem-the classification of handwritten numerals. As a result of our work we assign two feature extraction criteria to the employed network for a significant estimation of its efficiency.

关键词： Feature extraction Neural networks pattern recognition Error probability Character recognition Iterative algorithms Circuit synthesis data mining pattern analysis Performance analysis

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Cursive script recognition applied to the processing of bank cheques

Cursive script recognition applied to the processing of bank...

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international conference on Document Analysis and recognition

作者： D. Guillevic C.Y. Suen CENPARMI GM-606 Concordia University Montreal QUE Canada

A method for recognizing unconstrained handwritten words belonging to a small static lexicon is proposed. Our computational theory is based on a psychological model of the reading process of a fast reader. The method we propose is global in its nature and avoid the difficult segmentation stage of common word recognition techniques. Our computational theory has been applied to the processing of handwritten bank cheques, whose problem domain is that of unconstrained handwriting, unlimited writers in a small static lexicon. Current results seem comparable to those published in the literature and support our computational theory.

关键词： databases Handwriting recognition Law Legal factors data mining NIST Character recognition Histograms Psychology pattern recognition

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Zoning invariant holistic recognizer for hybrid recognition of handwriting

Zoning invariant holistic recognizer for hybrid recognition ...

引用

international conference on Document Analysis and recognition

作者： R.K. Powalka N. Sherkat R.J. Whitrow Department of Computing Nottingham Trent University Nottingham UK

The paper describes a holistic recognizer developed for use in a hybrid recognition system. The recognizer uses information about the word shape. As this information is strongly related to word zoning, care is taken to avoid limitations resulting from the inaccuracy of zone detection. The recognizer uses a very simple set of features and a fuzzy set based pattern matching technique. This aims to increase its robustness, but also causes problems with disambiguation of the results. A verification mechanism, using letter alternatives as compound features, is introduced. The letter alternatives are obtained from a segmentation based recognizer coexisting in the hybrid system. The holistic recognizer is found capable of outperforming the segmentation based one, despite the remaining disambiguation problems. When working together in a hybrid system, the results are significantly higher than those of the individual recognizers. recognition results are reported and compared.

关键词： Handwriting recognition Bars Shape Encoding pattern recognition Fuzzy sets pattern matching Robustness Writing data mining

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