计算机工程与应用2019，Vol.55Issue(18)：34-37,4.DOI:10.3778/j.issn.1002-8331.1903-0286
融合PCA、LDA和SVM算法的人脸识别
Face Recognition Based on PCA,LDA and SVM Algorithms
摘要
Abstract
In order to improve the efficiency of face recognition, this paper proposes a face recognition method based on the fusion of PCA, LDA and SVM algorithms. The Principal Component Analysis(PCA)is used to transform the face image into a new feature space, which eliminates the correlation and noise between the features of the image and extracts the global feature of the face. In the experiment stage, this paper takes more projection directions to keep the original infor-mation as much as possible. Then the Linear Discriminant Analysis(LDA)algorithm is used to further project transform to reduce the data dimension. Support Vector Machine(SVM)is used to classify and recognize. In this paper, the advan-tages of PCA, LDA and SVM algorithms are combined and simulated on the ORL database. The results show that the rec-ognition rate of this method can reach 99.0%.关键词
人脸识别/主成分分析(PCA)/线性判别分析(LDA)/支持向量机(SVM)Key words
face recognition/Principal Component Analysis(PCA)/Linear Discriminant Analysis(LDA)/Support Vec-tor Machine(SVM)分类
信息技术与安全科学引用本文复制引用
徐竟泽,吴作宏,徐岩,曾建行..融合PCA、LDA和SVM算法的人脸识别[J].计算机工程与应用,2019,55(18):34-37,4.基金项目
国家自然科学基金(No.11547037,No.11604181) （No.11547037,No.11604181）
山东省研究生教育创新计划(No.01040105305) （No.01040105305）
山东科技大学教学研究项目(No.JG201506). （No.JG201506）
