@article{(Open Science Index):https://publications.waset.org/pdf/9999412, title = {Quantitative Analysis of PCA, ICA, LDA and SVM in Face Recognition}, author = {Liton Jude Rozario and Mohammad Reduanul Haque and Md. Ziarul Islam and Mohammad Shorif Uddin}, country = {}, institution = {}, abstract = {Face recognition is a technique to automatically identify or verify individuals. It receives great attention in identification, authentication, security and many more applications. Diverse methods had been proposed for this purpose and also a lot of comparative studies were performed. However, researchers could not reach unified conclusion. In this paper, we are reporting an extensive quantitative accuracy analysis of four most widely used face recognition algorithms: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) using AT&T, Sheffield and Bangladeshi people face databases under diverse situations such as illumination, alignment and pose variations. }, journal = {International Journal of Computer and Information Engineering}, volume = {8}, number = {9}, year = {2014}, pages = {1613 - 1616}, ee = {https://publications.waset.org/pdf/9999412}, url = {https://publications.waset.org/vol/93}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 93, 2014}, }