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Proceedings Paper

Context-driven text recognition by means of dictionary support
Author(s): Josua Boon; Frank Hoenes; Majdi Ben Hadj Ali
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Paper Abstract

This paper presents an alternative method for typed character recognition by way of the textual context. The approach here is word-oriented, and uses no a priori knowledge about typical appearance of characters. It leads back to an approach suggested by R. G. Casey where text recognition is considered as solving a substitution cipher, or cryptogram. Character images are considered only in order to distinguish or group (cluster) them. The recognition information used is provided by dictionaries. The overall procedure can be divided into three principle steps: (1) a ciphertext like symbolic representation of the text is generated. (2) in an initialization phase only a few but reliable word recognitions are striven for. The resulting partial symbol-character assignments are sufficient to initiate the following relaxation of the recognition process as the third step. Whereas Casey uses several ambiguous alternatives for word recognition, the approach here is based on acquiring a few, but reliable, recognition alternatives. Thus, instead of a spell check program, a dictionary with a heuristic-driven look- up control combined with an appropriate access mechanism is used.

Paper Details

Date Published: 23 March 1994
PDF: 11 pages
Proc. SPIE 2181, Document Recognition, (23 March 1994); doi: 10.1117/12.171124
Show Author Affiliations
Josua Boon, German Research Ctr. for Artificial Intelligence (DFKI) (Germany)
Frank Hoenes, German Research Ctr. for Artificial Intelligence (DFKI) (Germany)
Majdi Ben Hadj Ali, German Research Ctr. for Artificial Intelligence (DFKI) (Germany)

Published in SPIE Proceedings Vol. 2181:
Document Recognition
Luc M. Vincent; Theo Pavlidis, Editor(s)

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