Fingerprint Recognition Based on Coalition of Multi-Features

Abstract

This paper is representative to create a system of authentication depended on biometric confirmation. Different biometric methods are Face Recognition; Palm Recognition; Fingerprint Recognition; Face Recognition; voice Signature; Iris; User-Ids and Passwords. Our authentic system use fingerprint factor in its work. Because fingerprint is one of the most common biometric methods and ID of fingerprint recognition has been performed by in view of its unique features like: delta points, core point, and bifurcation points. Moreover, fingerprint is one of the greatest instances insecurity of biometric because it can recognize personal information and it is more protected than any other biometric ID system. The purpose of this paper is to achieve fingerprint recognition system based on Crossing Number (CN) method was utilized for minutiae extraction and coalition of 2D Wavelet Transform and 2D Gabor features extraction. The experiment the system based on coalition of 2D Wavelet filter and 2D Gabor wavelet transform feature the recognition rate of fingerprint recognition is 95.9 %. In matching process, we used Bhattacharyya distance. In this work four types of feature extraction techniques was performed and tested then compare between their results to get the most efficient method for used in the proposed system.