Enhanced biometric authentication technique using the binary information’s of fingerprint structural patterns

Abstract

This research proposes a new technique for an enhanced biometric authentication technique by converting binary to hexadecimal code from the binary pieces of information of fingerprint features. More investigates had done the biometric confirmation utilizing the primary highlights of the unique mark. The unique marks have different orientations, and it is too tricky to identify the fingerprint's unique marks precisely. Those investigations utilized profoundly muddled procedures like Hough Transform, ANN (Artificial Neural Network), FFT (Fast Fourier Transform), CNN (Convolution Neural Network), Etc. The convoluted methods are utilized to distinguish the unique mark parts (Ridges, Bifurcations, and Trifurcations, Etc.). It is hard to recognize the pieces of a unique mark for a few kinds (Arch, Whorl, and Loop) of finger impression. Henceforth the creator leans towards the Binary data to extricate the specific unique mark from the data set because the Binary data shifted relying upon the size and directions of particulars subtleties. The hexadecimal code is made utilizing the Binary data of a finger impression. The made hexadecimal code for all unique finger impression pictures of an information base is put away as formats. The made put away formats are utilized for coordinating with measure rather than information base to save time. At last, the proposed work gives 99.5% of exactness with superior.