Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/25471
Title: An approach to natural stroke extraction for off-line loosely-constrained handwritten Chinese characters
Authors: Yeung, DS
Fong, HS
Tsang, ECC
Shu, W
Wang, X
Keywords: Ambiguity handling
Fuzzy model matching
Fuzzy set partitioning
Natural stroke extraction
Off-line handwritten Chinese character recognition
Issue Date: 2003
Publisher: World Scientific
Source: International journal of pattern recognition and artificial intelligence, 2003, v. 17, no. 8, p. 1483-1513 How to cite?
Journal: International journal of pattern recognition and artificial intelligence 
Abstract: This paper proposes a new approach to extracting natural strokes from the skeletons of loosely-constrained, off-line handwritten Chinese characters. It admits the output substrokes from a previously proposed fuzzy substroke extractor as its inputs. By Identifying a number of expected ambiguities which include mutual similarities, unstable touches and joint/cross distortions, fuzzy stroke models are constructed and a "hit-all" fuzzy stroke matching strategy is pursued, Fuzzy partitioning technique is used to generate a ranked list of consistent stroke sets from the set of fuzzy strokes being identified, With this approach, a maximum of 20 distinct natural stroke classes can be extracted from each input character, together with an estimate on the actual count of strokes which compose the character. Our system offers a number of performance tuning capabilities such as the computation of the fuzzy scores of each extracted stroke, the adjustment on the fuzzy stroke model parameters, and the potential of incorporating one's personal writing styles into our methodology.
URI: http://hdl.handle.net/10397/25471
ISSN: 0218-0014
EISSN: 1793-6381
DOI: 10.1142/S0218001403002988
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