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Proceedings Paper

Genetic approach to the analysis of complex text formatting
Author(s): Jiangying Zhou; Daniel P. Lopresti; Jeffrey Zhou
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Paper Abstract

Traditional document analysis systems often adopt a top-down framework, i.e., they are composed of various locally interacting functional components, guided by a central control mechanism. The design of each component is determined by a human expert and is optimized for a given class of inputs. Such a system can fail when confronted by an input that falls outside its anticipated domain. This paper investigates the use of a genetic-based adaptive mechanism in the analysis of complex test formatting. Specifically, we explore a genetic approach to the binarization problem. As opposed to a single, pre-defined, 'optimal' thresholding scheme, the genetic-based process applies various known methods and evaluates their effectiveness on the input image. Individual regions are treated independently, while the genetic algorithm attempts to optimize the overall result for the entire page. Advantages and disadvantages of this approach are discussed.

Paper Details

Date Published: 7 March 1996
PDF: 12 pages
Proc. SPIE 2660, Document Recognition III, (7 March 1996); doi: 10.1117/12.234698
Show Author Affiliations
Jiangying Zhou, Panasonic Technologies, Inc. (United States)
Daniel P. Lopresti, Panasonic Technologies, Inc. (United States)
Jeffrey Zhou, Panasonic Technologies, Inc. (United States)

Published in SPIE Proceedings Vol. 2660:
Document Recognition III
Luc M. Vincent; Jonathan J. Hull, Editor(s)

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