Distorted Fingerprint Indexing Using Minutia Detail and Delaunay Triangle

This paper is concentrated on an accurate and efficient fingerprint indexing algorithm, which efficiently retrieves the top N possibly matched candidates from a huge database. In order to have ability of coping with distorted fingerprints, the proposed algorithm uses novel features, which are insensitive to distortion, formed by the Delaunay triangulation of minutiae set as the representation unit. These features include minutia detail and Delaunay triangle (its handedness, angles, maximum edge, and related angle between orientation field and edges). Experiments on database FVC 2000 and scanned fingerprints with heavy distortion show our algorithm considerably narrows down the search space in fingerprint databases and is also available for distorted fingerprints. We also compared with other indexing approaches, and results show our algorithm has a better performance, especially on fingerprints with heavy distortion. This algorithm has another significant advantage that is it provides the control points for fingerprint distortion compensation.