Abstract
An innovative Gabor-based Orthogonal Locality Sensitive Discriminant Analysis for face recognition is presented in this paper. This algorithm is based on a combination of Gabor wavelets representation of face images and a new Orthogonal Locality Sensitive Discriminant Analysis for face recognition. In this paper, a Gabor filter is first designed to extract the features from the whole face images, and then a new Orthogonal Locality Sensitive Discriminant Analysis, which is proposed to preserve the local geometrical structure by computing the mutually orthogonal basis functions iteratively, is used to subject these feature vectors onto locality subspace projection. Experiments based on the ORL face database demonstrate the effectiveness and efficiency of the new method. Results show that our new algorithm is robust to changes in illumination and facial expressions and poses. And it outperforms the other popular approaches reported in the literature and achieves a much higher accurate recognition rate.
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