基于支持向量机的手写体相似字识别

Recognition of Similar Chinese Handwriting by Support Vector Machine

本文提出对手写相似汉字进行识别的支持向量机方法。该方法与人工神经网络一样适用于小规模分类 ,但由于支持向量机依据结构风险最小化原则 ,因此泛化能力更强。并且 ,由于支持向量机算法是一个凸二次优化问题 ,能够保证找到的极值解就是全局最优解。本文用支持向量机算法对三组手写相似汉字进行了识别 ,取得了较好的结果。

This paper presents a recognition method of similar Chinese handwriting by support vector machine. This method can be used to small scale recognition, like artificial neural networks, but it has stronger generalization ability because the support vector machine theory is based on the minimization principle to structure risk. Because the algorithm of support vector machine is a convex quadratic optimization problem, the local optimal solution is certainly the global optimal one. This paper presents a sample to recognize three groups of similar Chinese handwritings with the algorithm of support vector machine and good results are obtained.