A fuzzy rule-based system for structure decomposition on handwritten Chinese characters
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In this paper, a fuzzy rule-based system for decomposing the structure of divisible handwritten Chinese characters is proposed. The decomposition is aimed at obtaining a radical that can be used as the preclassification information for handwritten Chinese character recognition (HCCR). We adopt the fuzzy set theory to deal with the recognition of the patterns. Fuzzy rules which represent the character structures are used to combine the extracted strokes into compound strokes or radicals. The capability of the system can be enhanced by increasing the fuzzy rules appropriately. An average of 95% recognition rate on the radical recognition of 542 test characters which are selected from the 100th samples of HCCRBASE was obtained.<<ETX>>
[1] Fang-Hsuan Cheng,et al. Research on Chinese OCR in Taiwan , 1991, Int. J. Pattern Recognit. Artif. Intell..
[2] A. Kandel,et al. Applicability of some fuzzy implication operators , 1989 .
[3] James B. Kuo,et al. A coded block adaptive neural network system with a radical-partitioned structure for large-volume Chinese characters recognition , 1992, Neural Networks.