A fingerprint image essentially consists of a set of minutiae on the plane. Minutiae are the terminations and bifurcations of ridge-lines in a fingerprint image. The ridge-lines, appearing in the foreground of the gray-scale topography, are separated by valley lines appearing in the background. In a fingerprint image, there exists a striking duality in the sense that the valley lines also have minutiae (terminations and bifurcations) and flow patterns similar to the ridge-lines. The ridge and valley characteristics, such as ridge and valley flow directions, inter-ridge and inter-valley distances, ridge and valley breaks, etc., are very useful properties that indicate the validity criteria of a minutia detected by any algorithm. Many Automatic Fingerprint Identification Systems (AFIS) are based on minutiae matching. Minutiae are the terminations and bifurcations of the ridge-lines in a fingerprint image. A fingerprint image that has undergone binarization, followed by thinning, in order to extract the minutiae, contains hundreds of minutiae, all of which are not so vivid and obvious in the original image. Thus, the set of minutiae that are well-defined and more prominent than the rest should have given higher relevance and importance in the process of minutiae matching. In this work, a method to assign a score value to each of the extracted minutiae is proposed, based on some topographical properties of a minutia. The score associated to a minutia signifies its genuineness and prominence. A minutia with a higher score value should be given higher priority in the matching scheme to yield better results.

Reference Paper: Determination of Minutiae Scores for Fingerprint Image Applications
Author’s Name: P. Bhowmick, A. Bishnu, B. B. Bhattacharya ., M. K. Kundu, C. A. Murthy and T. Acharya
Source: ISICAL

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