Finger vein extraction and authentication based on gradient feature selection algorithm

In present days, Authentication by means of biometrics systems is used for personal verifications. In spite of having existing technology in biometrics such as recognizing the fingerprints, voice/face recognition etc., the vein patterns can be used for the personal identification. Finger vein is a promising biometric pattern for personal identification and authentication in terms of its security and convenience. Finger vein has gained much attention among researchers to combine accuracy, universality and cost efficiency. We propose a method of personal identification based on finger-vein patterns. An image of a finger captured under infrared light contains not only the vein pattern but also irregular shading produced by the various thicknesses of the finger bones and muscles. The proposed method extracts the finger-vein pattern from the unclear image by using gradient feature extraction algorithm and the template matching by Euclidean distance algorithm. The better vein pattern algorithm has to be introduced to achieve the better Equal Error Rate (EER) of 0.05% comparing to the existing vein pattern recognition algorithms.