{"title":"彩色人脸识别的扩展PCA和LDA","authors":"Qiong Kang, Lingling Peng","doi":"10.1109/ISIC.2012.6449777","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new method for color face recognition. We extract the first, second and third channels of each color image and use PCA and LDA to get a score of each channel, then we use a combine scheme to attain a final score and use this final score to classify test samples. In order to check the performance of our method, we conduct experiments on Georgia Tech (GT) color face database, at the same time, we compare our method with PCA and LDA, and experiment results show that our methods take better performance.","PeriodicalId":393653,"journal":{"name":"2012 International Conference on Information Security and Intelligent Control","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"An extended PCA and LDA for color face recognition\",\"authors\":\"Qiong Kang, Lingling Peng\",\"doi\":\"10.1109/ISIC.2012.6449777\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a new method for color face recognition. We extract the first, second and third channels of each color image and use PCA and LDA to get a score of each channel, then we use a combine scheme to attain a final score and use this final score to classify test samples. In order to check the performance of our method, we conduct experiments on Georgia Tech (GT) color face database, at the same time, we compare our method with PCA and LDA, and experiment results show that our methods take better performance.\",\"PeriodicalId\":393653,\"journal\":{\"name\":\"2012 International Conference on Information Security and Intelligent Control\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Information Security and Intelligent Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIC.2012.6449777\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Information Security and Intelligent Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIC.2012.6449777","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An extended PCA and LDA for color face recognition
In this paper, we propose a new method for color face recognition. We extract the first, second and third channels of each color image and use PCA and LDA to get a score of each channel, then we use a combine scheme to attain a final score and use this final score to classify test samples. In order to check the performance of our method, we conduct experiments on Georgia Tech (GT) color face database, at the same time, we compare our method with PCA and LDA, and experiment results show that our methods take better performance.