Fragmented edge structure coding for Chinese writer identification

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• 作者：Jing Wen ; ^{wj@cqu.edu.cn}  ; [Author Vitae] ; Bin Fang  ; [Author Vitae] ; JunLin Chen  ; [Author Vitae] ; YuanYan Tang  ; [Author Vitae] ; HengXin Chen  ; [Author Vitae]
• 关键词：Text-independent writer identification ; Edge fragments ; Encoding feature ; Probability distribution function ; Chi-square distance ; Pattern recognition
• 刊名：Neurocomputing
• 出版年：2012
• 期刊代码：95_09252312
• 类别：cp
• 出版时间：1 June, 2012
• 卷：86
• 期：Complete
• 页码：45-51
• 文件大小：1292 K

摘要

As a branch of biometrics, handwriting-based writer identification is an active research topic in pattern recognition. This paper presents a theoretically very simple, yet efficient, multiresolution approach to off-line, text-independent Chinese writer identification based on edge structure code (ESC) distribution feature and nonparametric discrimination of sample. ESC distribution feature is based on probability distribution function, which characterizes the frequent structures distribution of edge fragments on multiple scales. Experiments were conducted on an open HIT-MW database which is widely used for performance evaluation. Experimental results show that the proposed method was able to improve the identification accuracy.