{"title":"基于改进模主成分分析的人脸识别","authors":"Xingfu Zhang","doi":"10.1109/ICICSE.2009.29","DOIUrl":null,"url":null,"abstract":"The technology of face recognition has been widely applied to many fields such as identity authentication. A New Improvement for Face Recognition Using MMPCA is presented in this paper. The proposed algorithm when compared with conventional modular PCA algorithm is different in the computation of image mean value and the recognition process. Comparison of the two algorithms in different face databases proves that the proposed algorithm is more effective and robust than conventional modular PCA algorithm under the large variations in lighting direction and facial expression. The authors also point out that 2DPCA is a special case of improved algorithm, no matter in the process of dimension reduction or recognition.","PeriodicalId":193621,"journal":{"name":"2009 Fourth International Conference on Internet Computing for Science and Engineering","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Face Recognition Based on Modified Modular Principal Component Analysis\",\"authors\":\"Xingfu Zhang\",\"doi\":\"10.1109/ICICSE.2009.29\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The technology of face recognition has been widely applied to many fields such as identity authentication. A New Improvement for Face Recognition Using MMPCA is presented in this paper. The proposed algorithm when compared with conventional modular PCA algorithm is different in the computation of image mean value and the recognition process. Comparison of the two algorithms in different face databases proves that the proposed algorithm is more effective and robust than conventional modular PCA algorithm under the large variations in lighting direction and facial expression. The authors also point out that 2DPCA is a special case of improved algorithm, no matter in the process of dimension reduction or recognition.\",\"PeriodicalId\":193621,\"journal\":{\"name\":\"2009 Fourth International Conference on Internet Computing for Science and Engineering\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Fourth International Conference on Internet Computing for Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICSE.2009.29\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Fourth International Conference on Internet Computing for Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICSE.2009.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Face Recognition Based on Modified Modular Principal Component Analysis
The technology of face recognition has been widely applied to many fields such as identity authentication. A New Improvement for Face Recognition Using MMPCA is presented in this paper. The proposed algorithm when compared with conventional modular PCA algorithm is different in the computation of image mean value and the recognition process. Comparison of the two algorithms in different face databases proves that the proposed algorithm is more effective and robust than conventional modular PCA algorithm under the large variations in lighting direction and facial expression. The authors also point out that 2DPCA is a special case of improved algorithm, no matter in the process of dimension reduction or recognition.