Abstract:

As it is difficult to recognize the facial image with a random rotation angle in a plane,a method integrating 2DNPP with Trace transform is proposed for the extraction and recognition of rotation-invariant features. In this method,first,the image is dealt with through the first and the second Trace transform. Then,the matching calculation of the double Trace feature is carried out,thus achieving a feature,which not only is robust to in-plane rotation but also can preserve most information of the raw image. Finally,the classification and dimension reduction are conducted by means of 2DNPP. The proposed method is compared with SIFT,pseudo-Zernike methods on frontal,rotary and noisy facial image databases. The results show that,on the ORL image database with a random rotation angle,the proposed method has a recognition rate of 96% as well as a strong robustness to white noise.

Key words: face recognition, Trace transform, rotation invariance, feature extraction