Zhanghui Chen
ABSTRACT
In this paper, a popular snake model is enhanced by considering the guiding image force and speeded up by incorporating Genetic Algorithm. It has been applied to segment the radicals in offline handwritten Chinese characters. Testing results show that the proposed approach can effectively decompose the radicals with overlaps and connections from the characters with various layout structures. The segmentation accuracy reaches 94.91% and the average running time is around 0.05 second per character.
- Wang, A. B., and Fan, K. C. Optical recognition of handwritten Chinese characters by hierarchical radical matching method. Pattern Recognition 34 (2001) 15--35.Google Scholar
Cross Ref
- Ip, W. W. S., Chung, K. F. L., and Yeung, D. S. Offline Handwritten Chinese Character Recognition via Radical Extraction and Recognition. 4th International Conference on Document Analysis and Recognition, 1997, pp. 185--189. Google ScholarDigital Library
- Ibáñez, O., Barreira, N., Santos J., and Penedo, M. G. Genetic approaches for topological active nets optimization. Pattern Recognition 42 (2009) 907--917. Google ScholarDigital Library
Index Terms
- Effective radical segmentation of offline handwritten Chinese characters by using an enhanced snake model and Genetic Algorithm
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