AN APPLIED COARSE CLASSIFICATION SCHEME AND ANALYSIS

摘要：

An applied coarse classification scheme for handwritten Chinese character is presented in this paper. Four-side code feature is employed as coarse feature and RBF neural network is used as classifier in this experiment. In contrast to Euclidean distance as the measurement of similarity used in conventional method, RBF(radial basis function) neural network is better to fit the data of each class. In this way the precision rate is up to 93.20％. Analyzing the misclassified characters, overlap area classification method is applied in experiment and precision rate is up to 96.18％. Experimental results show that proposed method is applied and has satisfying performance on coarse classification of handwritten Chinese character.

关键词： Coarse classification Handwritten Chinese character RBF neural network Overlap area classification

作者: HONG-RUI LI FANG YANG LI-NA ZUO XUE-DONG TIAN

作者单位: College of Mathematics and Computer Science, Hebei University, Baoding 071002, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 1740-1743

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）