一种基于仿生识别的脱机手写体汉字识别方法

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Abstract In this paper, biomimetic pattern recognition is employed to construct double weighted elliptical neuron sequence which is used to extract basic stroke segments to cover the handwritten Chinese character image. The topological property of the stroke segment neurons is analyzed. An image of handwritten Chinese characters is transformed into geometric figures composed by six styles of Chinese character strokes with fault tolerance. To imitate typing methods of human Chinese characters font code, the style, the number, the position, the number of joint and the crossover of stroke neurons with redundant fault tolerant shapes are counted. Data structures of characteristic knowledge of handwritten Chinese characters are built. Handwritten Chinese characters from SCUTIRAC HCCLIB are tested and the results confirm the proposed method has the ability of cognizing handwritten Chinese characters.

Key words： Biomimetic Pattern Recognition Neuron Sequence Characteristic Knowledge Fault Tolerance

Received: 11 September 2006

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TP391.43

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	Articles by authors
	WANG JianPing
	LI WeiTao
	WANG JinLing
	WANG XiHui
	CHENG Yu

Cite this article:

WANG JianPing,LI WeiTao,WANG JinLing等. Research on Offline Handwritten Chinese Characters RecognitionBased on Biomimetic Recognition[J]. , 2008, 21(1): 62-71.

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http://manu46.magtech.com.cn/Jweb_prai/EN/ OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2008/V21/I1/62

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