Offline handwritten Chinese character recognition by radical decomposition
ACM Transactions on Asian Language Information Processing (TALIP)
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Proceedings of the 2012 ACM symposium on Document engineering
International Journal of Distance Education Technologies
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Despite the facts that Chinese characters are composed of radicals and Chinese usually formulate their knowledge of Chinese characters as a combination of radicals, very few studies have focused on a character decomposition approach to recognition, i.e., recognizing a character by first extracting and recognizing its radicals. In this paper, such an approach is adopted and the problem of how to extract radical sub-images from character images is particularly addressed. A radical extraction algorithm based on deformable templates (DTs) has been developed. The application of DTs to Chinese character recognition is a novel one and concepts like goodness of character decomposition have been exploited to formulate appropriate energy terms and to devise cost effective minimization schemes for the problem. The advantage of the character decomposition approach is demonstrated by feeding the extracted radical images to an adopted structural based Chinese character recognizer whose outputs are then combined to produce the class label of the input character. Simulation results show that the performance of the adopted Chinese character recognition system can be improved significantly when character decomposition approach is used.