计算机工程与应用2017，Vol.53Issue(16)：155-160,6.DOI:10.3778/j.issn.1002-8331.1703-0161
LBP特征和改进Fisher准则的人脸识别
Face recognition based on LBP feature and improved Fisher criterion.
摘要
Abstract
In order to improve the performance of face recognition system, the criterion function of LDRC algorithm is improved and applied to the Fisher classifier, a new face recognition algorithm based on LBP feature and improved Fisher criterion is proposed. Firstly, the standard LBP histogram feature of each face image is extracted. Secondly, the extracted LBP features are input into the improved Fisher classifier to obtain the optimal projection matrix and the voting result matrix. Thirdly, the class number corresponding to the maximum value of the voting result matrix is solved, which is regarded as the final recognition result. Finally, those experiments are done in FERET and AR face database respectively. The final results show that the face recognition rate has been significantly improved compared with the traditional methods.关键词
人脸识别/Fisher准则/直方图特征/特征提取/投影矩阵Key words
face recognition/Fisher criterion/histogram feature/feature extraction/projection matrix分类
信息技术与安全科学引用本文复制引用
刘斌,徐岩,米强,徐运杰..LBP特征和改进Fisher准则的人脸识别[J].计算机工程与应用,2017,53(16):155-160,6.基金项目
山东科技大学教学研究项目(No.JG201506) （No.JG201506）
山东科技大学研究生教育创新项目(No.KDYC13026,No.KDYC15019) （No.KDYC13026,No.KDYC15019）
山东省研究生教育创新计划项目(No.01040105305). （No.01040105305）
