Palmprint recognition based on Gabor wavelets and 2-dimensional PCA&PCA

This paper presents a novel palmprint recognition method using Gabor wavelets and 2-Dimensional Principal Component Analysis (2-DPCA) and PCA. Different from the Gabor wavelets plus PCA method, the proposed method uses the 2-DPCA to generate feature space for accurately extracting palmprint features, and PCA is used as further feature dimensional reduction. Simulation results on PolyU Palmprint Database show that the proposed method is superior to the Gabor plus PCA method in palmprint recognition and identification.