Performance Enhancement of PCA-based Face Recognition System via Gender Classification Method

Performance Enhancement of PCA-based Face Recognition System via Gender Classification Method

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Part of #Performance Enhancement of PCA-based Face Recognition System via Gender Classification Method# :

Publishing year : 2010

Conference : Sixth Conference of the Machine and Image Processing

Number of pages : 6

Abstract: In this paper, we demonstrate that gender estimation technique can increase the accuracy of face recognition system. If the gender of the input image can be estimated correctly before it is recognized and compared with images of the same sex, errors between males and females during recognition step can be eliminated. Consequently, the accuracy will be boosted. Principal Component Analysis (PCA) has been used in our experiment. To be compatible with this recognizer, the proposed gender estimation algorithm also uses a non-training procedure. A part of FERET database including 292 male and 264 female images has been used. Experimental results show 7% accuracy enhancement for PCA recognition system in the presence of gender estimation.