Gabor and Haar Wavelets Mixed Usage in Face Recognition Based on Direct Linear Discriminant Analysis and Support Vector Machine

In this paper, beside studying in fields of electronic, image processing, computer vision, face recognition, filtering, wavelet transform, linear discriminant analysis and support vector machine, a new method for face recognition has been proposed. First, feature vectors are obtained from raw face images using Gabor wavelets. Next, the extracted feature vectors are mapped to a low dimensional subspace using Haar wavelets. Then, direct linear discriminant analysis technique is used for more compressing and splitting data obtained from the previous part. Finally, these obtained data are sent to support vector machine classifier for classification and then recognition of new images. The proposed method was examined using the FERET database. Experimental results illustrate effectiveness of this method against other related works in terms of recognition rate.