基于笔划方向特征和非对称分布的手写体汉字识别  

The Recognition of Handwritten Chinese Character by Stroke Orientation and Asymmetric Distribution

作　　者：李国宏[1] 施鹏飞[1] 

机构地区：[1]上海交通大学图像处理与模式识别研究所,上海200030

出　　处：《上海交通大学学报》2005年第12期1988-1992,共5页Journal of Shanghai Jiaotong University

基　　金：国家自然科学基金资助项目(60075007)

摘　　要：基于笔划方向特征和非对称分布的手写体汉字识别模型,提出一种从手写体汉字骨骼图像上提取分叉点的有效改进算法,保证笔划提取的可靠性,并直接从笔划结构上计算统计识别特征矢量;采用主向量空间的非对称参数分布模型计算距离测度.实验表明,基于笔划方向特征和非对称分布的统计识别模型具有优良的识别性能.An approach based on stroke orientation and asymmetric distribution model about feature parameter was proposed, which incorporates structural feature into statistical strategy. An improvement to the algorithm for extracting fork points from skeleton images defends the reliability of stroke extraction. The feature vector for statistical recognition is extracted directly from stroke structure, and the asymmetric distribution model is applied to compute distances. The experimental results indicate that the proposed system is effective to handwritten Chinese character recognition.

关 键 词：汉字识别 手写体汉字 笔划 非对称分布 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]