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Proceedings Paper

Handprinted character recognition based on complex stroke structures
Author(s): Hsin-Chang Yang
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Paper Abstract

The printed areas of a handprinted character with thick strokes were replaced by a frame formed by bended ellipses to represent the character efficiently and emulate the high order receptive fields in later visual system. Each bended ellipse maximally fits the local stroke pattern and captures the position, orientation and topology information contained in the local stroke pattern. Complex stroke structures are represented by concept neurons which each contains several bended ellipses. The craft of concept neurons provides an uniform representation for receptive fields in any order. The model uses these concept neurons in searching their corresponding neurons in the template frame. To obtain the correspondence, a global affine transform followed by a local distorting process are used to align the two frames. To afford topology preservation the topology order of the character is generated explicitly. The classification is achieved by examining the similarity between the topology order of the handprinted pattern and the template patterns.

Paper Details

Date Published: 22 December 1999
PDF: 7 pages
Proc. SPIE 3967, Document Recognition and Retrieval VII, (22 December 1999); doi: 10.1117/12.373501
Show Author Affiliations
Hsin-Chang Yang, Chang Jung Univ. (Taiwan)


Published in SPIE Proceedings Vol. 3967:
Document Recognition and Retrieval VII
Daniel P. Lopresti; Jiangying Zhou, Editor(s)

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