Feature extraction based on fuzzy bidirectional maximum margin criterion for face recognition

摘要：

This paper proposes a new method for feature extraction and recognition, namely, the fuzzy bidirectional maximum margin criterion (FBMMC) based on the maximum margin criterion and fuzzy set theory. In FBMMC, a membership grade matrix is calculated by the FKNN algorithm, and then the membership grades are incorporated into the formulation of the scatter matrices to formulate the row and column directional fuzzy scatter matrices. Using the fuzzy scatter matrix, FBMMC performs fuzzy image MMC in the row and column directions simultaneously. Experiments on the ORL and Yale face databases show the effectiveness of the proposed FBMMC based feature extraction method.

关键词： Maximum margin criterion (MMC) Fuzzy bidirectional maximum margin criterion (FBMMC) Feature extraction Face recognition

作者: Haishun Du Xiaobo Guo Fan Zhang Jianjun Zhao

作者单位: Institute of Image Processing and Pattern Recognition Henan University Kaifeng Henan,China School of mechanical and power engineering Hennan Polytechnic University Jiaozuo Henan, China Institute of Image Processing and Pattern Recognition Henan University Kaifeng Henan, 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: 215-219

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）