{"title":"PCA type algorithm applied in face recognition","authors":"S. Nedevschi, Ioan Radu Peter, Adina Mandrut","doi":"10.1109/ICCP.2012.6356181","DOIUrl":null,"url":null,"abstract":"One of the widely used approaches in image recognition is principal component analysis (PCA) because of the good balance between the simplicity and speed of the algorithm and the results obtained by using it. In the last years many variants of PCA were developed: two dimensional PCA, two directional two dimensional PCA, extended two dimensional PCA and extended two dimensional two directional PCA, the last one developed by the first two authors of the present paper. In this paper we go further with this study by considering a mixed approach between E2DPCA and diagonal PCA. The mixed approach not only takes approximately the same amount of time for training and testing as the classical approach, but also gives better recognition accuracy for some of the PCA algorithm variants.","PeriodicalId":406461,"journal":{"name":"2012 IEEE 8th International Conference on Intelligent Computer Communication and Processing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 8th International Conference on Intelligent Computer Communication and Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCP.2012.6356181","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
One of the widely used approaches in image recognition is principal component analysis (PCA) because of the good balance between the simplicity and speed of the algorithm and the results obtained by using it. In the last years many variants of PCA were developed: two dimensional PCA, two directional two dimensional PCA, extended two dimensional PCA and extended two dimensional two directional PCA, the last one developed by the first two authors of the present paper. In this paper we go further with this study by considering a mixed approach between E2DPCA and diagonal PCA. The mixed approach not only takes approximately the same amount of time for training and testing as the classical approach, but also gives better recognition accuracy for some of the PCA algorithm variants.