Abstract：Inspired by prior knowledge of face images' approximate symmetry, an algorithm based on symmetric Gabor features and sparse representation was proposed, which was successfully applied into face recognition in the paper. At first, mirror transform was performed on face images to get their mirror images, with which the face images could be decomposed into odd-even symmetric faces. Then, Gabor features were extracted from both odd faces and even faces to get the Gabor odd-even symmetric features，which could be fused via a weighting factor to generate the new features. At last, the newly obtained features were combined to form an over-complete dictionary which was used by sparse representation to classify the faces. The experimental results on AR and FERET face databases show that the new method can achieve high accuracy even when face images are under expression, pose and illumination variations.
何玲丽 李文波. 基于对称Gabor特征和稀疏表示的人脸识别[J]. 计算机应用, 2014, 34(2): 550-552.
HE Lingli LI Wenbo. Face recognition based on symmetric Gabor features and sparse representation. Journal of Computer Applications, 2014, 34(2): 550-552.
2014, Vol. 34 
