Abstract
This paper presents a new pattern recognition framework for face recognition based on the combination of Radon and wavelet transforms, which is invariant to variations in facial expression, and illumination. It is also robust to zero mean white noise. The technique computes Radon projections in different orientations and captures the directional features of face images. Further, the wavelet transform applied on Radon space provides multiresolution features of the facial images. Being the line integral, Radon transform improves the low-frequency components that are useful in face recognition. For classification, the nearest neighbor classifier has been used. Experimental results using FERET, ORL, Yale and YaleB databases show the superiority of the proposed method with some of the existing popular algorithms.
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