Face Recognition Based on Steerable PyramidTransform and LS-SVM

摘要：

An efficient local appearance feature extraction method based on S-P wavelet transform and Least Square Support Vector Machine (LS-SVM) is proposed for face recognition to reduce the dimensionality of facial image and improve the recognition rate.As a latest multi-resolution analysis method,steerable pyramid transform (S-P) has improved directional elements with anisotropy and better ability to represent sparsely edges and other singularities.By utilizing S-P wavelet transform to extract features from facial images and LS-SVM to classify facial images based on features,the proposed scheme has been evaluated by carrying out experiments on the wellknown ORL face database.Experimental results show that the proposed method provides a better representation of the class information,and obtains much higher recognition accuracies in real-world situations including changes in pose,expression and illumination.

关键词： S-P wavelet transform LS-SVM face recognition ORL face database

作者: Lin Dong Huixun Zhao

作者单位: Dept.of Communication Engineering,Engineering College of APF Xian,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Network Technology(ICCNT 2011)(2011第三届IEEE计算机与网络技术国际会议)

会议地点: 太原

会议语种:英文

页码: 564-568

在线出版日期: 2011-02-26（万方平台首次上网日期，不代表论文的发表时间）