{"title":"基于DWFT特征提取的系数共现直方图与ONPP人脸识别","authors":"Xiaoshan Liu, Minghui Du, Lianwen Jin","doi":"10.1109/ICICISYS.2009.5357734","DOIUrl":null,"url":null,"abstract":"The important step of face recognition based on subspace method is to obtain powerful features. In this paper, we propose a novel feature extraction technique based on discrete wavelet frame transform(DWFT), which capture the information about relationship between each high frequency subband and the low frequency subband of the decomposed image at the corresponding level. In the feature space, we use orthogonal neighborhood preserving profections (ONPP) algorithm to reduce dimension. experimental results show that the proposed algorithm is effective in face recognition. Comparisons with the other approachs are also provided.","PeriodicalId":206575,"journal":{"name":"2009 IEEE International Conference on Intelligent Computing and Intelligent Systems","volume":"320 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Coefficients' co-occurrence histogram of DWFT based feature extration with ONPP for face recognition\",\"authors\":\"Xiaoshan Liu, Minghui Du, Lianwen Jin\",\"doi\":\"10.1109/ICICISYS.2009.5357734\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The important step of face recognition based on subspace method is to obtain powerful features. In this paper, we propose a novel feature extraction technique based on discrete wavelet frame transform(DWFT), which capture the information about relationship between each high frequency subband and the low frequency subband of the decomposed image at the corresponding level. In the feature space, we use orthogonal neighborhood preserving profections (ONPP) algorithm to reduce dimension. experimental results show that the proposed algorithm is effective in face recognition. Comparisons with the other approachs are also provided.\",\"PeriodicalId\":206575,\"journal\":{\"name\":\"2009 IEEE International Conference on Intelligent Computing and Intelligent Systems\",\"volume\":\"320 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Conference on Intelligent Computing and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICISYS.2009.5357734\",\"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 IEEE International Conference on Intelligent Computing and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICISYS.2009.5357734","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Coefficients' co-occurrence histogram of DWFT based feature extration with ONPP for face recognition
The important step of face recognition based on subspace method is to obtain powerful features. In this paper, we propose a novel feature extraction technique based on discrete wavelet frame transform(DWFT), which capture the information about relationship between each high frequency subband and the low frequency subband of the decomposed image at the corresponding level. In the feature space, we use orthogonal neighborhood preserving profections (ONPP) algorithm to reduce dimension. experimental results show that the proposed algorithm is effective in face recognition. Comparisons with the other approachs are also provided.