System authentication using minutiae and fingercode features of fingerprint

System authentication based on explicit detection of complete ridge structures in the fingerprint is difficult. Ridge structures cannot be completely characterized by minutiae. Further, a minutia based matching has difficulty in quickly matching two fingerprint images containing different number of unregistered minutiae points. The proposed matching algorithm uses both minutiae and texture information. It uses a bank of Gabor filters to capture both local and global details in a fingerprint as a compact fixed length finger code. Matching is achieved with the help of Euclidean distance between the query and template image, hence is extremely fast. Experimental results show that combination of minutiae and texture based (local as well as global) score matching leads to substantial improvement in the overall matching performance even at low resolutions