A Comparison of Principal Component Analysis and Adaptive Principal Component Extraction for Palmprint Recognition

This paper investigates palmprint recognition using Principal Component Analysis (PCA) and the Adaptive Principal component EXtraction (APEX) which is one of the PCA techniques involving neural network. Through implementing the PCA and APEX algorithms for extracting features and applying them to palmprint recognition with two classifiers, Euclidean distance and Hamming distance, it was made known that APEX algorithm is efficient in palmprint recognition and the rate of recognition given by APEX is way more than PCA.