{"title":"基于Gabor特征的人脸特征提取完全fisher判别框架","authors":"Zhiqiang Zeng","doi":"10.1109/WCSP.2009.5371732","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a novel feature extraction approach using Gabor feature based complete fisher discriminant algorithm (GCFD). Four main steps are involved in the proposed GCFD: (i) Gabor features of different scales and orientations are extracted by the convolution of Gabor filter bank and original gray images; (ii) Complete fisher discriminant algorithm (CFD) is used for feature dimensionality reduction and to extract all discrimination information; (iii) Feature fusion algorithm and Euclidean distance based nearest neighbor classifier are finally used for classification. (iv)Simulation results show the effectiveness of our proposed GCFD.","PeriodicalId":244652,"journal":{"name":"2009 International Conference on Wireless Communications & Signal Processing","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Gabor feature-based complete fisher discriminant framework for facial feature extraction\",\"authors\":\"Zhiqiang Zeng\",\"doi\":\"10.1109/WCSP.2009.5371732\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a novel feature extraction approach using Gabor feature based complete fisher discriminant algorithm (GCFD). Four main steps are involved in the proposed GCFD: (i) Gabor features of different scales and orientations are extracted by the convolution of Gabor filter bank and original gray images; (ii) Complete fisher discriminant algorithm (CFD) is used for feature dimensionality reduction and to extract all discrimination information; (iii) Feature fusion algorithm and Euclidean distance based nearest neighbor classifier are finally used for classification. (iv)Simulation results show the effectiveness of our proposed GCFD.\",\"PeriodicalId\":244652,\"journal\":{\"name\":\"2009 International Conference on Wireless Communications & Signal Processing\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Wireless Communications & Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCSP.2009.5371732\",\"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 International Conference on Wireless Communications & Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCSP.2009.5371732","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Gabor feature-based complete fisher discriminant framework for facial feature extraction
In this paper, we propose a novel feature extraction approach using Gabor feature based complete fisher discriminant algorithm (GCFD). Four main steps are involved in the proposed GCFD: (i) Gabor features of different scales and orientations are extracted by the convolution of Gabor filter bank and original gray images; (ii) Complete fisher discriminant algorithm (CFD) is used for feature dimensionality reduction and to extract all discrimination information; (iii) Feature fusion algorithm and Euclidean distance based nearest neighbor classifier are finally used for classification. (iv)Simulation results show the effectiveness of our proposed GCFD.