Hough transform-based technique for fingerprint alteration detection and classification

Fingerprint alteration is a major threat to automatic fingerprint identification systems, especially in border security control system. A Hough transform-based method for detection and classification of altered fingerprint is presented here. Altered fingerprints consists of huge amount of broken ridges due to different process used for making alteration and this in turn causes large number of ridge ending. The amount of ridge endings is different in different types of altered fingerprints. Hough transform-based method proposed in this paper utilises the variation in ridge ending density as a feature for detection and classification of altered fingerprints. The ridge end points in normal and altered fingerprints are collinear even though they are distributed randomly in the image space. Due to the variation of ridge ending density, the number of collinear ridge end points varies with respect to normal and different types of alteration. Making use of this, a threshold is selected in the Hough accumulator to perform detection and classification of fingerprint alteration. A method for the classification of scar present in altered and normal fingerprints is also proposed here.