Contrast enhancement and feature extraction algorithms of finger knucle print image for personal recognition

The Finger-Knuckle-Print (FKP) which is defined with its rich texture is becoming a new challenge to identify persons. In this paper, we propose a new algorithm for personal recognition including two main steps. Firstly, an enhancement algorithm based on Adaptive Histogram Equalization (AHE) is considered to improve the contrast of input FKP images. Secondly, a new algorithm is proposed to extract minutiae from enhanced FKP image. Simulation results showed that our proposed algorithm performs better than others existing methods with an FAR close to 0% and FRR values ranging from 87.5% to 100%.