{"title":"Face recognition using neural networks","authors":"N. Jamil, S. Lqbal, N. Iqbal","doi":"10.1109/INMIC.2001.995351","DOIUrl":null,"url":null,"abstract":"In this paper we depict an experiment to the face recognition problem by combining eigenfaces and neural network. Eigenfaces are applied to extract the relevant information in a face image, which are important for identification. Using this we can represent face pictures with several coefficients (about twenty) instead of having to use the whole picture. Neural networks are used to recognize the face through learning correct classification of the coefficients calculated by the eigenface algorithm. The network is first trained on the pictures from the face database, and then it is used to identify the face pictures given to it. Eight subjects (persons) were used in a database of 80 face images. A recognition accuracy of 95.6% was achieved with vertically oriented frontal views of a human face.","PeriodicalId":286459,"journal":{"name":"Proceedings. IEEE International Multi Topic Conference, 2001. IEEE INMIC 2001. Technology for the 21st Century.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"171","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. IEEE International Multi Topic Conference, 2001. IEEE INMIC 2001. Technology for the 21st Century.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INMIC.2001.995351","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 171
Abstract
In this paper we depict an experiment to the face recognition problem by combining eigenfaces and neural network. Eigenfaces are applied to extract the relevant information in a face image, which are important for identification. Using this we can represent face pictures with several coefficients (about twenty) instead of having to use the whole picture. Neural networks are used to recognize the face through learning correct classification of the coefficients calculated by the eigenface algorithm. The network is first trained on the pictures from the face database, and then it is used to identify the face pictures given to it. Eight subjects (persons) were used in a database of 80 face images. A recognition accuracy of 95.6% was achieved with vertically oriented frontal views of a human face.