Optimized Palm Recognition Using Cuckoo Search Algorithm

Abstract: Palm recognition system is used for segmented the images in order to improve the performance and reliability. For this palm recognition used some data sets. These data sets based upon the location of the friction ridge area. In this work we gather a database from 30 persons. Then it used active shape model algorithm after that cuckoo search algorithm is used for optimized result. In this proposed work, we used gabor filtration method. At the end trained coefficients are compared with the query coefficients and extract the matched image from trained dataset. It concludes that our proposed scheme which used active shape model, cuckoo search algorithm & Gabor filtration gives better results. The experimental results demonstrated that the proposed palm recognition system achieves a recognition accuracy of 98.4% and with false rejection rate (FRR) of = 0.77% & false acceptance rate (FAR) of = 0.77%.

Keywords: Biometrics, Palmprint, Cuckoo, False Acceptance Rate (FAR), False Rejection Rate (FRR).