A Novel Palmprint Recognition Algorithm Based on PCA&FLD

Recently palmprint recognition received many researchers´ attention because of it ´s low resolution and cheap devices. As other features recognition, algebraic feature is the prevailing method for palmprint recognition. PCA and FLD features belong to this feature, and they all have successfully been used for palmprint recognition. PCA (principal component analysis) is the optimal dimension compression technique based on second-order information in the sense of mean-square error. FLD is one of the most popular linear classification techniques for feature detection. In this paper, we proposed a novel method based on traditional PCA&FLD method. In this method, PCA is not only used for reducing dimension, the PCA feature is also used again to make a fusion with FLD feature in recognition stage. We imply our method to PolyU Palmprint database and the experiment result shows that the novel method is better