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Adaptive Content Recognition

  • Book
  • © 2004

Overview

Editors:
  1. Andreas Dengel

    1. Knowledge Management Department, German Research Center for Artificial Intelligence (DFKI) GmbH, Kaiserslautern, Germany

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  2. Markus Junker

    1. German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany

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  3. Anette Weisbecker

    1. Institute for Human Factors and Technology Management, University of Stuttgart, Stuttgart, Germany

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 2956)

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Table of contents (18 chapters)

  1. Front Matter

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  2. Error Tolerant Color Deskew

    • Dirk Woitha, Dietmar Janich
    Pages 1-13

  3. Adaptive Threshold

    • Dirk Woitha, Dietmar Janich
    Pages 14-25

  4. Neighbourhood Related Color Segmentation Based on a Fuzzy Color Classification TooL

    • Bernhard Frei, Marin Hund, Markus Schnitzlein
    Pages 26-36

  5. Improving Image Processing Systems by Artificial Neural Networks

    • R. Rebmann, B. Michaelis, G. Krell, U. Seiffert, F. Püschel
    Pages 37-64

  6. Adaptive Segmentation of Multicoloured Documents without a Marked Background

    • G. Eberhardt, S. Römer, J. Saedler
    Pages 65-90

  7. Recognition of Short Handwritten Texts

    • Michael Boldt, Christopher Asp
    Pages 91-102

  8. Handwritten Address Recognition Using Hidden Markov Models

    • Anja Brakensiek, Gerhard Rigoll
    Pages 103-122

  9. Adaptive Combination of Commercial OCR Systems

    • Elke Wilczok, Wolfgang Lellmann
    Pages 123-136

  10. Component-Based Software Engineering Methods for Systems in Document Recognition, Analysis, and Understanding

    • Oliver Höß, Oliver Strauß, Anette Weisbecker
    Pages 137-152

  11. A Component-Based Framework for Recognition Systems

    • Matthias Middendorf, Carsten Peust, Johannes Schacht
    Pages 153-165

  12. smartFIX: An Adaptive System for Document Analysis and Understanding

    • Bertin Klein, Andreas R. Dengel, Andreas Fordan
    Pages 166-186

  13. How Postal Address Readers Are Made Adaptive

    • Hartmut Schäfer, Thomas Bayer, Klaus Kreuzer, Udo Miletzki, Marc-Peter Schambach, Matthias Schulte-Austum
    Pages 187-215

  14. A Tool for Semi-automatic Document Reengineering

    • Jens Drawehn, Christoph Altenhofen, Mirjana StaniÅ¡ić-Petrović, Anette Weisbecker
    Pages 216-234

  15. Inspecting Document Collections

    • Ulrich Bohnacker, Jürgen Franke, Heike Mogg-Schneider, Ingrid Renz
    Pages 235-251

  16. Introducing Query Expansion Methods for Collaborative Information Retrieval

    • Armin Hust
    Pages 252-280

  17. Improving Document Transformation Techniques with Collaborative Learned Term-Based Concepts

    • Stefan Klink
    Pages 281-305

  18. Passage Retrieval Based on Density Distributions of Terms and Its Applications to Document Retrieval and Question Answering

    • Koichi Kise, Markus Junker, Andreas Dengel, Keinosuke Matsumoto
    Pages 306-327

  19. Results of a Survey about the Use of Tools in the Area of Document Management

    • Christoph Altenhofen, Haigo R. Hofmann, Thomas Kieninger, Mirjana StaniÅ¡ić-Petrović
    Pages 328-354

  20. Back Matter

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Keywords

About this book

The amounts of information that are ?ooding people both at the workplace and in private life have increased dramatically in the past ten years. The number of paper documents doubles every four years, and the amount of information stored on all data carriers every six years. New knowledge, however, increases at a considerably lower rate. Possibilities for automatic content recognition in various media and for the processing of documents are therefore becoming more important every day. Especially in economic terms, the e?cient handling of information, i.e., ?- ing the right information at the right time, is an invaluable resource for any enterprise, but it is particularly important for small- and medium-sized ent- prises. The market for document management systems, which in Europe had a volume of approximately 5 billion euros in 2000, will increase considerably over the next few years. The BMBF recognized this development at an early stage. As early as in 1995, it pooled national capabilities in this ?eld in order to support research on the automatic processing of information within the framework of a large collaborative project (READ) involving both industrial companies and research centres. Evaluation of the results led to the conclusion that research work had been successful, and, in a second phase, funding was provided for the colla- rative follow-up project Adaptive READ from 1999 to 2003. The completion of thesetwoimportantlong-termresearchprojectshascontributedsubstantiallyto improving the possibilities of content recognition and processing of handwritten, printed and electronic documents.

Editors and Affiliations

  • Knowledge Management Department, German Research Center for Artificial Intelligence (DFKI) GmbH, Kaiserslautern, Germany

    Andreas Dengel

  • German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany

    Markus Junker

  • Institute for Human Factors and Technology Management, University of Stuttgart, Stuttgart, Germany

    Anette Weisbecker

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