Shape Recognition by Fuzzy Distance Measure

摘要：

A novel shape recognition method based on fuzzy distance measure is proposed. A fuzzy set is defined on the feature vector space according to each training class, so the distance between an unknown shape and the class centroid is measured by a fuzzy distance based on the membership function. Another significant contribution of this paper is the method of constructing membership function using the statistical features of training class. Our shape recognition method is a minimum distance method in nature, but compared with the minimum distance method using common distance measure, fuzzy distance measure improves the accuracy rate of recognition greatly. The accuracy improved either compared with KNN classifier.

关键词： accuracy improved either compared with KNN classifier

作者: Wenjing Qi Xueqing Li Lei Tang Zunyi Xu

作者单位: School of computer science and Technology, Shandong Jianzhu University, Jinan, China School of compu School of computer science and Technology, Shandong University, Jinan, China School of computer science and Technology, Shandong Jianzhu University, Jinan, China

会议类型: 国际会议

会议名称: 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

会议地点: 厦门

会议语种:英文

页码: 737-741

在线出版日期: 2010-10-29（万方平台首次上网日期，不代表论文的发表时间）