Face Recognition Based on Curvelet Transform and LS-SVM

As a latest multiresolution analysis method, curvelet transform has improved directional elements with anisotropy and better ability to represent sparsely edges and other singularities along curves. To reduce the dimensionality of facial image and improve the recognition rate, a face recognition system based on curvelet transform and Least Square Support Vector Machine (LS-SVM) has been developed in this paper, which uses curvelet transform to extract features from facial images first, and then uses LS-SVM to classify facial images based on features. The proposed method has been evaluated by carrying out experiments on the well-known ORL face database. The results show that the correct recognition rate is up to 96%, and the computational speed is faster. Index Terms —curvelet transform, LS-SVM, face recognit –ion, ORL face database