Document Analysis Systems V

5th International Workshop, DAS 2002 Princeton, NJ, USA, August 19–21, 2002 Proceedings

Editors:

ISBN: 978-3-540-44068-0 (Print) 978-3-540-45869-2 (Online)

Table of contents (58 chapters)

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  1. OCR Features and Systems

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      Pages 1-12

      Relating Statistical Image Differences and Degradation Features

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      Pages 13-24

      Script Identification in Printed Bilingual Documents

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      Pages 25-36

      Optimal Feature Extraction for Bilingual OCR

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      Pages 37-48

      Machine Recognition of Printed Kannada Text

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      Pages 49-52

      An Integrated System for the Analysis and the Recognition of Characters in Ancient Documents

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      Pages 53-57

      A Complete Tamil Optical Character Recognition System

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      Pages 58-61

      Distinguishing between Handwritten and Machine Printed Text in Bank Cheque Images

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      Pages 62-65

      Multi-expert Seal Imprint Verification System for Bankcheck Processing

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      Pages 66-69

      Automatic Reading of Traffic Tickets

  2. Handwriting Recognition

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      Pages 70-81

      A Stochastic Model Combining Discrete Symbols and Continuous Attributes and Its Application to Handwriting Recognition

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      Pages 82-94

      Top-Down Likelihood Word Image Generation Model for Holistic Word Recognition

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      Pages 95-105

      The Segmentation and Identification of Handwriting in Noisy Document Images

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      Pages 106-110

      The Impact of Large Training Sets on the Recognition Rate of Off-line Japanese Kanji Character Classifiers

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      Pages 111-114

      Automatic Completion of Korean Words for Open Vocabulary Pen Interface

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      Pages 115-118

      Using Stroke-Number-Characteristics for Improving Efficiency of Combined Online and Offline Japanese Character Classifiers

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      Pages 119-122

      Closing Gaps of Discontinuous Lines: A New Criterion for Choosing the Best Prolongation

  3. Classifiers and Leaning

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      Pages 123-133

      Classifier Adaptation with Non-representative Training Data

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      Pages 134-144

      A Learning Pseudo Bayes Discriminant Method Based on Difference Distribution of Feature Vectors

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      Pages 145-156

      Increasing the Number of Classifiers in Multi-classifier Systems: A Complementarity-Based Analysis

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      Book Chapter

      Pages 157-166

      Discovering Rules for Dynamic Configuration of Multi-classifier Systems

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