Finger vein recognition using linear Kernel Entropy Component Analysis

Based on the previous research, Kernel Entropy Component Analysis (KECA) is introduced as a more appropriate method than Kernel Principal Component Analysis (KPCA) for face recognition. In this paper, an algorithm using KECA is proposed to merit finger vein recognition. The proposed algorithm is then compared to Principal Component Analysis (PCA) and Different types of KECA in order to determine the most appropriate one in terms of finger vein recognition.