Two-dimensional FDA Algorithm for Face Recognition Based on Weighted Symmetry Image
Tao Jing-cao, Ding Qing-sheng · Jisuanji gongcheng · 2009
【Abstract】A new method based on two-dimensional FDA by combining with weighted-symmetry face is proposed for face recognition. This new algorithm introduces the even symmetry samples and the odd symmetry samples of face images. The even symmetry samples and the odd symmetry samples are used to form new face samples by a weighted actor. The optimal feature projection space of the new face samples is calculated through two-dimensional FDA, algorithm to classify the extracted features. This new method uses effectively not only the advantages of two-dimensional FDA but also the symmetrical properties of facial images to achieve better recognition rate. The influence of different weighted factor make is analyzed in this paper. Choosing the optimal weighted factor achieves the best performance. Experimental results on ORL database show the efficiency of the new method.