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1 April 1998 Detection of deleted patterns in handwritten digits using topological and geometrical image features
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Proceedings Volume 3305, Document Recognition V; (1998) https://doi.org/10.1117/12.304627
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States
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.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Misako Suwa, Satoshi Naoi, and Yoshinobu Hotta "Detection of deleted patterns in handwritten digits using topological and geometrical image features", Proc. SPIE 3305, Document Recognition V, (1 April 1998); https://doi.org/10.1117/12.304627
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