FINGER VEIN FEATURE EXTRACTION USING DISCRETIZATION
Finger vein is a promising biometric pattern for personal identification due to its high security over other biometric identification techniques. Compared with other biometrics such as fingerprint, face and iris, finger vein patterns exhibits universality, uniqueness, permanence and measurability characteristic. Furthermore, finger vein is a living body identification which means that only vein in living finger can be captured and used for identification. The standard practice of various research works in finger vein identification focuses on feature extraction and classification process. However, the selection of meaningful features is highly depends on the early pre processing stage. Acquiring useful features from finger vein in order to reflect the identity of the individual is the main issues for identification. This research aims at improving the scheme of finger vein identification based on Maximum Curvature Directional Feature (MCDF) discretization where it is a combination of Maximum Curvature Points feature extraction method and Directional based feature extraction method. Discretization is adopted for systematically represented extracted features from MCDF for identification purposed. Experimental results show that the performance of the proposed methods is above 90%