基于主曲线的脱机手写数字识别

该文提出了一种基于主曲线的脱机手写数字识别方法.该方法将主曲线及知识约简算法运用于识别模型中.主曲线是主成份分析的非线性推广,它是通过数据分布"中间"并满足"自相合"的光滑曲线.它较好地反映了数据分布的结构特征.粗糙集理论的知识约简是从决策表中获取决策(分类)规则的有效工具.本文将主曲线用于训练数据的特征提取,根据主曲线的特征生成决策表;利用我们提出的知识约简算法对决策表进行处理,自动获得分类规则.这种方法既符合人的识别习惯,又克服了利用统计特征识别所带来的不足.实验结果表明了该方法能有效提高手写数字的识别率,为脱机手写数字识别的研究提供了一条新途径.

Off-Line Handwritten Digit Recognition Based on Principal Curves

The paper proposes a method of off-line handwritten digit recognition based on principal curves.The method uses principal curves and reduction of knowledge to extract the structural features of digits and design a classifier.Principal curves are nonlinear generalizations of principal component analysis.They are smooth self-consistent curves that pass through the "middle" of the distribution.They preferably reflect the structural features of the data.Reduction of knowledge is the efficient tool of obtaining classification rules from a decision table.Firstly principal curves are used to extract the structural features of training data.Secondly the classification features are chosen by analyzing the structural features of principal curves in detail,then we set up the decision table that consists of these classification features.Finally we automatically attain classification rules by attribute and attribute value reduction.The method accords with the recognition habit of human and overcomes the disadvantage of statistical features.The experimental result indicates that the method can effectively improve the recognition rate of off-line handwritten digits,and provides a new approach to the research for off-line handwritten digit recognition.