Finger print false minutiae extraction using standard deviation normalization

Abstract

It is important to extract minutiae of a fingerprint for the implementation of an auto fingerprint identification system. A critical step in studying the statistics of fingerprint minutiae is to reliably extract minutiae from the fingerprint images. Minutiae are discontinues spots in finger print pattern, more precisely terminations, bifurcations, lakes, independent ridges, dots or islands, spurs, and crossover. fingerprint images are rarely of perfect quality. They may be degraded and corrupted due to variations in skin and impression conditions. Thus, image enhancement techniques are employed prior to minutiae extraction to obtain a more reliable estimation of minutiae locations. The study represented in this paper copes with minutiae extraction. In This paper we present a method for minutiae extraction based on standard deviation normalization. A complete normalization fingerprint minutiae extraction has been developed using matlab. This method has been developed and shown very good results in terms of efficiency and time required.