Palmprint recognition based on wavelet decomposition and PCA
Haifeng Sang · Jisuanji yingyong yanjiu · 2008
This paper proposed a new method for feature extraction of palmprint.This method improved upon feature extraction speed of palmprint under without reducing recognition rate.First,the original palmprint images became the lower resolution images using wavelet decomposing.Second,used principal components analysis,reduced the lower resolution palmprint images dimensionality.This low dimensional feature subspace was called Eigenpalms.At last,those samples of a training set and a testing set were projected this Eigenpalms.The experiment result shows that much training time has been saved by using this algorithm in features extracting recognition.