Research of multi-scales Gabor uncertainty in face recognition

摘要

In face recognition multi-scales Gabor features contain a large amount of redundant information and the value of the features are different from each other. The paper proposes multi-scales Gabor uncertainty weighted fusion algorithm in face recognition, multi-scales Gabor features were used to show facial features firstly, and then weights and uncertainties were calculated to get the last facial feature by multi-scales uncertainty weighted fusion algorithm. At the same time 2DPCA method was exploited to construct the linear subspace and Euclidean distance based classifier was adopted for classification. With the ORL database, the experimental results indicated that compared with the use of 2DPCA, traditional wavelet and Gabor wavelet feature extraction method, the proposed method in this paper had obtained better recognition rate.