Effective radical segmentation of offline handwritten Chinese characters by using an enhanced snake model and Genetic Algorithm

Authors:
Zhanghui Chen;Baoyao Zhou;Shan Dong
Affiliations:
Chinese Academy of Sciences;EMC Labs China;Chinese Academy of Sciences
Venue:
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Year:
2012

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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.