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Proceedings Paper

Detection of deleted patterns in handwritten digits using topological and geometrical image features
Author(s): Misako Suwa; Satoshi Naoi; Yoshinobu Hotta
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Paper Abstract

One of the critical problems of an off-line handwritten character reader system is determining which patterns to read and which to ignore, as a form or a document contains not only characters but also spots and deletions. As long as they don't fit conditions for rejection, they cause recognition errors. Particularly, patterns of deleted single-character are difficult to be distinguished from a character, because their sizes are almost the same as that of a character and their shapes have variety. In this article, we proposed a method to detect such deletions in handwritten digits using topological and geometrical image- features suitable for detecting them; Eular number, pixel density, number of endpoint, maximum crossing counts and number of peaks of histogram. For precise detection, thresholds of the image features are adaptively selected according to their recognition results.

Paper Details

Date Published: 1 April 1998
PDF: 8 pages
Proc. SPIE 3305, Document Recognition V, (1 April 1998); doi: 10.1117/12.304627
Show Author Affiliations
Misako Suwa, Fujitsu Labs. Ltd. (Japan)
Satoshi Naoi, Fujitsu Labs. Ltd. (Japan)
Yoshinobu Hotta, Fujitsu Labs. Ltd. (Japan)


Published in SPIE Proceedings Vol. 3305:
Document Recognition V
Daniel P. Lopresti; Jiangying Zhou, Editor(s)

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