期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2011
卷号：4
期号：1
出版社：SERSC
摘要：This paper deals with Face recognition using Single training sample which is a new challenging problem in machine vision. In the proposed method, first four different representation of face are generated using Gabor filters which vary in angle. Then a Base-classifier is assigned for each of them and also for original image. Finally EMV technique combines the Base-classifiers. EMV behaves like MV but chooses the vote of the Base-classifier assigned to original image as winner class when there is multiple winner class. Experimental results on ORL face dataset, show an improvement about 2%, 4% and 5% than 2DPCA, (PC)2A and PCA respectively
关键词：Face Recognition; Nearest Neighbor; Base-Classifier; Enhanced Majority ;Voting. Small Sample Size Problem
