Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/14281
Title: Two-stage segmentation of unconstrained handwritten Chinese characters
Authors: Zhao, S
Chi, Z 
Shi, P
Yan, H
Keywords: Character segmentation
Chinese character recognition
Decision trees
Fuzzy decision rules
Image preprocessing
Unconstrained handwritten Chinese characters
Issue Date: 2003
Publisher: Elsevier
Source: Pattern recognition, 2003, v. 36, no. 1, p. 145-156 How to cite?
Journal: Pattern recognition 
Abstract: Correct segmentation of handwritten Chinese characters is crucial to their successful recognition. However, due to many difficulties involved, little work has been reported in this area. In this paper, a two-stage approach is presented to segment unconstrained handwritten Chinese characters. A handwritten Chinese character string is first coarsely segmented according to the background skeleton and vertical projection after a proper image preprocessing. With several geometric features, all possible segmentation paths are evaluated by using the fuzzy decision rules learned from examples. As a result, unsuitable segmentation paths are discarded. In the fine segmentation stage that follows, the strokes that may contain segmentation points are first identified. The feature points are then extracted from candidate strokes and taken as segmentation point candidates through each of which a segmentation path may be formed. The geometric features similar to the coarse segmentation stage are used and corresponding fuzzy decision rules are generated to evaluate fine segmentation paths. Experimental results on 1000 Chinese character strings from postal mail show that our approach can achieve a reasonable good overall accuracy in segmenting unconstrained handwritten Chinese characters.
URI: http://hdl.handle.net/10397/14281
ISSN: 0031-3203
EISSN: 1873-5142
DOI: 10.1016/S0031-3203(02)00041-9
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