Perfect histogram matching PCA for face recognition |
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Authors: | Ana-Maria Sevcenco Wu-Sheng Lu |
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Affiliation: | 1.Department of Electrical and Computer Engineering,University of Victoria,Victoria,Canada |
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Abstract: | We present an enhanced principal component analysis (PCA) algorithm for improving rate of face recognition. The proposed pre-processing method, termed as perfect histogram matching, modifies the image histogram to match a Gaussian shaped tonal distribution in the face images such that spatially the entire set of face images presents similar facial gray-level intensities while the face content in the frequency domain remains mostly unaltered. Computationally inexpensive, the perfect histogram matching algorithm proves to yield superior results when applied as a pre-processing module prior to the conventional PCA algorithm for face recognition. Experimental results are presented to demonstrate effectiveness of the technique. |
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