基于纹理分析的汉字笔迹识别研究

Jun Feng, Xu Gao
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引用次数: 1

摘要

汉字笔迹自动识别作为一种基于行为的个人识别技术,已成为模式识别和机器学习研究领域的热点。有许多关键问题值得研究。本文讨论了基于纹理分析的汉字笔迹识别技术。首先,建立了一个实用的中文手写图像样本库CHSL2007,对现有算法进行比较和进一步研究。然后探讨了基于纹理分析的特征提取方法,并利用了成对支持向量机分类器。将基于Gabor滤波的纹理分析实验结果与基于DB6小波滤波的纹理分析实验结果进行了比较,结果表明前者更适合于CHSL2007上的笔迹识别。最后,确定了CHSL2007的单张识别率为99.50%以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on Chinese handwriting identification based on texture analysis
As a kind of behavior-based personal identification techniques, automated Chinese handwriting identification becomes a hot topic in pattern recognition and machine learning research area. There are lots of key issues worthy researching. In this paper, the Chinese handwriting identification technology based on texture analysis is discussed. Firstly, a practical Chinese handwriting image samples library CHSL2007 is established for the comparison of exist algorithms and further research. Then the methods of feature extraction based on texture analysis are explored and the pairwise SVM classifier is utilized. The experiment results of texture analysis based on Gabor filter is compared with DB6 wavelet filter and demonstrate that the former is more suitable for handwriting identification on CHSL2007. Finally, the sheet recognition rate is defined and can be arrived at above 99.50% for CHSL2007.
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