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Adaptive Combination of Commercial OCR Systems

  • Chapter
Reading and Learning

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

Abstract

Combining multiple classifiers to achieve improved recognition results has become a popular technique in recent years. As for OCR systems, most investigations focus on fusion strategies on the character level. This paper describes a flexible framework for the combination of result strings which are the common output of commercial OCR systems. By synchronizing strings according to geometrical criteria, incorrect character segmentations can be avoided, while character recognition is improved by classical combination rules like Borda Count or Plurality Vote. To reduce computing time, further expert calls are stopped as soon as the quality of a temporary combination result exceeds a given threshold. The system allows easy integration of arbitrary new OCR systems and simplifies the determination of optimal system parameters by analyzing the input data at hand. Quantitative results are shown for a two-recognizer system, while the framework allows an arbitrary number of experts.

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Author information

Authors and Affiliations

  1. Océ Document Technologies GmbH, Constance, Germany

    Elke Wilczok & Wolfgang Lellmann

Authors
  1. Elke Wilczok
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  2. Wolfgang Lellmann
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Editor information

Editors and Affiliations

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

    Andreas Dengel

  2. German Research Center for Artificial Intelligence (DFKI), P.O.Box 2080, 67608, Kaiserslautern, Germany

    Markus Junker

  3. Institute for Human Factors and Technology Management, University of Stuttgart, Nobelstraße 12, 70569, Stuttgart, Germany

    Anette Weisbecker

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© 2004 Springer-Verlag Berlin Heidelberg

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Wilczok, E., Lellmann, W. (2004). Adaptive Combination of Commercial OCR Systems. In: Dengel, A., Junker, M., Weisbecker, A. (eds) Reading and Learning. Lecture Notes in Computer Science, vol 2956. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24642-8_8

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  • DOI: https://doi.org/10.1007/978-3-540-24642-8_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21904-0

  • Online ISBN: 978-3-540-24642-8

  • eBook Packages: Springer Book Archive

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