{"title":"一种基于单幅图像的人脸识别新算法","authors":"NuTao Tan, Lei Huang, Chang-ping Liu","doi":"10.1109/CCPR.2008.54","DOIUrl":null,"url":null,"abstract":"Face recognition, which is an active research area in pattern recognition, has made great progress in recent years. Its performance that based on multiple face images is satisfying, but it is remain poor when only a single face image is used to training. Accordingly, we propose a new algorithm of face recognition that based on a single face image in this paper. The new algorithm can be divided into three steps: first, we compute horizontal and vertical edge images from the gray image; then, local binary pattern histogram is extracted from those two edge images; finally, elastic matching is used to classification. Experimental result on some standard face databases show that our proposed method can substantially improves the recognition performance and is robustness to pose, illumination and expression.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Novel Algorithm for Face Recognition Based on a Single Image\",\"authors\":\"NuTao Tan, Lei Huang, Chang-ping Liu\",\"doi\":\"10.1109/CCPR.2008.54\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Face recognition, which is an active research area in pattern recognition, has made great progress in recent years. Its performance that based on multiple face images is satisfying, but it is remain poor when only a single face image is used to training. Accordingly, we propose a new algorithm of face recognition that based on a single face image in this paper. The new algorithm can be divided into three steps: first, we compute horizontal and vertical edge images from the gray image; then, local binary pattern histogram is extracted from those two edge images; finally, elastic matching is used to classification. Experimental result on some standard face databases show that our proposed method can substantially improves the recognition performance and is robustness to pose, illumination and expression.\",\"PeriodicalId\":292956,\"journal\":{\"name\":\"2008 Chinese Conference on Pattern Recognition\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Chinese Conference on Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCPR.2008.54\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Chinese Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCPR.2008.54","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Algorithm for Face Recognition Based on a Single Image
Face recognition, which is an active research area in pattern recognition, has made great progress in recent years. Its performance that based on multiple face images is satisfying, but it is remain poor when only a single face image is used to training. Accordingly, we propose a new algorithm of face recognition that based on a single face image in this paper. The new algorithm can be divided into three steps: first, we compute horizontal and vertical edge images from the gray image; then, local binary pattern histogram is extracted from those two edge images; finally, elastic matching is used to classification. Experimental result on some standard face databases show that our proposed method can substantially improves the recognition performance and is robustness to pose, illumination and expression.