关键词: 人脸识别, 离散余弦变换, 二维主成分分析, 二维线性鉴别分析, 加权融合

Abstract: Aiming at the limitation of the single face feature in face recognition and the lack of discriminative information of 2DPCA, a weighted fusion algorithm of face recognition based on 2DPCA and 2DLDA is proposed, which is according to the complementary idea. Firstly, the method of DCT is used to compress and reconstruct the original face image to filter out the middle and high frequency part that the human eye is not sensitive to in the image. Next, the face feature is extracted via the way of 2DPCA. Then, the discriminative face feature of the original face image is also extracted based on 2DLDA. At last, an adaptive weight selection method is proposed to fuse two kinds of face features and realize the classification recognition. The experimental results on ORL and YALE face database show that the proposed algorithm is effective.

Key words: face recognition, discrete cosine transform, two-dimensional principal component analysis, two-dimensional linear discriminant analysis, weighted fusion