{"title":"模糊积分混合n特征提取在人脸识别中的应用","authors":"J. Haddadnia, K. Faez","doi":"10.1109/VIPROM.2002.1026635","DOIUrl":null,"url":null,"abstract":"This paper introduces an efficient method for human face recognition that employs a set of different kinds of feature domains with RBF neural network classifiers, and which is denoted the hybrid N-feature (HNF) human face recognition. A combination of RBF neural network classifiers with fuzzy integral has been proposed to achieve face classification with higher performance. The feature extractor projects the face images in each appropriately selected transform domain in parallel. Experimental results on the ORL database confirm that the proposed method lends itself to higher classification accuracy relative to existing techniques.","PeriodicalId":223771,"journal":{"name":"International Symposium on VIPromCom Video/Image Processing and Multimedia Communications","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Hybrid N-feature extraction with fuzzy integral in human face recognition\",\"authors\":\"J. Haddadnia, K. Faez\",\"doi\":\"10.1109/VIPROM.2002.1026635\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces an efficient method for human face recognition that employs a set of different kinds of feature domains with RBF neural network classifiers, and which is denoted the hybrid N-feature (HNF) human face recognition. A combination of RBF neural network classifiers with fuzzy integral has been proposed to achieve face classification with higher performance. The feature extractor projects the face images in each appropriately selected transform domain in parallel. Experimental results on the ORL database confirm that the proposed method lends itself to higher classification accuracy relative to existing techniques.\",\"PeriodicalId\":223771,\"journal\":{\"name\":\"International Symposium on VIPromCom Video/Image Processing and Multimedia Communications\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Symposium on VIPromCom Video/Image Processing and Multimedia Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VIPROM.2002.1026635\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on VIPromCom Video/Image Processing and Multimedia Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VIPROM.2002.1026635","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hybrid N-feature extraction with fuzzy integral in human face recognition
This paper introduces an efficient method for human face recognition that employs a set of different kinds of feature domains with RBF neural network classifiers, and which is denoted the hybrid N-feature (HNF) human face recognition. A combination of RBF neural network classifiers with fuzzy integral has been proposed to achieve face classification with higher performance. The feature extractor projects the face images in each appropriately selected transform domain in parallel. Experimental results on the ORL database confirm that the proposed method lends itself to higher classification accuracy relative to existing techniques.