Face Recognition Using Binary Structure-Based Feature Selection
Xiao Guang Hu · 2010
This paper proposes a binary structure feature selection(BFS) for face recognition.In the proposed method,all classes are combined in pairs.Based on the two-class classifier,the most suitable features for discriminating these two classes are chosen to form a feature-selected space.During the test on an unknown sample image,similarities between the unknown image and all training classes are calculated in the feature-selected space.The unknown image is thus judged to belong to the class which shows the highest similarity. Performance of the method has been tested with the ATT and AR face databases.The results show that, compared with other methods,the proposed technique can achieve higher recognition rate with a low feature dimension.