FKP biometrics for human authentication using Gabor Wavelets

Automated security is one of the major concerns of modern times. Secure and reliable authentication systems are in great demand. A biometric trait like Finger Knuckle Print (FKP) of a person is unique and secure. In this paper, we propose a human authentication system based on FKP image of a person. We apply Gabor Wavelet on pre-processed FKP image. Then we identify the peak points in Gabor Wavelet graph. The successive distances between those points are calculated and are stored in a vector. Now, the elements in distance vector stored in database and that of input image are compared. Such a match is considered to be success if the difference between two such elements is lesser than the threshold value. Now, the probability of success is computed. The person is authenticated based on the value of computed probability. The proposed system has the FAR of about 1.24% and FRR as 1.11%.