Score level fusion of major and minor finger knuckle patterns based symmetric sum-based rules for person authentication

This paper present a novel system for person authentication based on score level fusion of Minor and Major dorsal finger knuckle patterns. In the proposed method, the adaptive single scale retinex method is used to extract the reflectance and the illumination of Major and Minor traits respectively, also the binarized statistical image features method is used to extract normalized histogram features. Furthermore, the Cosine Mahalanobis distance is used in the matching stage. Moreover, a multi-biometric system based score level fusion has been proposed. In attempt to enhance the performance recognition, the symmetric sum-based rules based on triangular norms are applied. The system is evaluated on the publically Minor/Major knuckle database. Experiments conducted on this database achieved good results. Besides, the proposed system outperforms the previous methods given in the state of the art.