Fingerprint Identification Using Modified Gabor Filter

Abstract

Fingerprints have been used as biometrics for personal identification or verification since a century ago. Although no exactly the same fingerprint from distinct identities was found, a perfect system for automatic fingerprint identification does not exist. The technique described here obviates the need for extracting minutiae points to match fingerprint images. This paper implements a Modified Gabor Filter (MGF). A circular tessellation of filtered image is then used to construct the ridge feature map. The fingerprint matching is based on the Euclidean distance between two corresponding feature vectors. This method can lessen noise, improving contrast between ridge and valley and also have tolerance to translation and rotation. Our system can increase the quality of image fingerprint. The achievement rate percentage of recognition is 85%.
Keywords: Biometrics, Modified Gabor filters, fingerprints, matching.