Abstract
In this paper, we propose a generation of feature image for face recognition. Feature image is generated using Discrete Cosine Transform (DCT), which tries to best classify different face images by maximizing the individual difference between face images. Low, Mid, and High frequency components of DCT are used to hold different information of face by providing a local description of different facial components such as detailed smooth region description and, effective edge representation. Reduction in different frequency components is achieved using statistical measure such as standard deviation. A comparison of proposed work with other standard methods is done on ORL face datasets. An experimental result shows a significant improvement of the proposed scheme.
Published Version
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