A Fusion Technique for The Multimodal Biometric System - Wincy, J. Anne; Raj, Y. Jacob Vetha (International Journal of Computer Sciences and Engineering, 2018)
Biometric recognition is the challenging area because security and user authentication is necessary for any login purpose. To identify a person, physiological characteristics are most widely used. This paper proposed a new fusion technique for the integration of finger knuckle print, palmprint and face biometrics. The present study concentrated on the multimodal biometric system due to its benefits. Initially the region of interest was obtained for the biometric traits. Then the features are extracted using Speeded Up Robust Features (SURF). Fusion of finger knuckle print, palmprint and face are done at score level using MeRank fusion rule. The MeRank technique uses classification result as well as matching scores of each trait. The performance of the proposed technique is evaluated and experimental results demonstrated that the fusion technique achieved 98.84% of accuracy for the multimodal biometric system.