Improved Face Recognition Approach Using Gabor Wavelet and Adaboost Algorithm

A new approach is proposed to improve face recognition in the paper. The accurate face is detected by the position relation of the face and the eyes. The face features are extracted using the Gabor wavelet and the Adaboost algorithm is used to detect the face and the eyes. In the actual detection of the face, the face is probably inclining, and then we correct the detected face according to the positions of two eyes. The difference size surround function in the Retinex theory is used against illumination to improve the robustness of face recognition. The similarity of the faces is detected by the cosine and distance of face feature vectors. To improve the recognition speed and accurate, a new match algorithm based on Euclidean distance and the vector cosine is proposed. The recognition results are good performed by the experiments.