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ReaD. Recognition + Documentanalysis. Erkennungssysteme + Dokumentanalyse. Version 0.3 Abschlussbericht

By U. Lemmer, C. Steigner, T. Blaudeck and Koblenz-Landau Univ. (Germany)

Abstract

The READ project is a co-operation of ten German partners from the industrial and research sector to develop new methods and products for document processing and document recognition applications. The work done by the University of Koblenz focused on rule-based off-line recognition of cursive script in massively disturbed recognition situations. We developed a knowledge representation language based on feature-terms (feature structures) and specialised for pattern recognition purposes. Based on this representation language we realised a general inference system kernel, a developing platform for such inference systems, a recognition system for cursive script, and methods for automated knowledge acquisition (rule generation, learning) and a specific aim of transforming the above mentioned knowledge representation into a more efficient but less powerful one. The developed methods can be helpful for a wide range of applications in document processing and will especially improve recognition results for cursive script text documents under strong deformations and noise. The specific rule based approach chosen here represents a new kind of solution for cursive script recognition with significant additional and alternative features compared with existing approaches for example based on Hidden Markov Models and other methods. (orig.)SIGLEAvailable from TIB Hannover: F98B1915+a / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekBundesministerium fuer Bildung, Wissenschaft, Forschung und Technologie, Bonn (Germany)DEGerman

Topics: 09H - Computer software, programming, 09K - Pattern recognition, image processing, PATTERN RECOGNITION, CURSIVE SCRIPT RECOGNITION, INFERENCE, EXPERT SYSTEMS, CONTROL, FEATURE-TERMS, KNOWLEDGE REPRESENTATION, LEARNING
Year: 1998
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Provided by: OpenGrey Repository
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