Authors: Hui Ma; Oluwatoyin P. Popoola; Shuli Sun
Addresses: College of Electronic Engineering, Heilongjiang University, Harbin 150080, China ' Systems Engineering Department, Faculty of Engineering, University of Lagos, Nigeria ' College of Electronic Engineering, Heilongjiang University, Harbin 150080, China
Abstract: The use of personal identity authentication systems with multi-modal biometrics has been proposed in order to increase the performance and robustness against environmental variation and fraudulent attacks. This paper presents a novel fingerprint and finger vein identity authentication system based on multi-route detection. Firstly, two classifiers are designed for fingerprint image and finger vein image respectively. Then extracted feature vectors from the first stage are then concatenated to make the third classifier. The final result is achieved by the fusion of the three classifiers' recognition results at the decision level. Experimental results show that this algorithm not only overcomes the limitations of single-modal biometrics, but also effectively improves the recognition performance of the system.
Keywords: biometrics; concatenated classifiers; finger vein verification; decision level fusion; fingerprint images; minutiae feature; personal identity; identity authentication; feature extraction; recognition performance.
International Journal of Biometrics, 2015 Vol.7 No.3, pp.271 - 285
Received: 19 Mar 2015
Accepted: 22 Jul 2015
Published online: 24 Sep 2015 *