A BROAD SURVEY ON FEATURE EXTRACTION METHODS FOR FINGERPRINT IMAGE ANALYSIS

This paper focused on the study of various feature extraction techniques applied for fingerprint identification, verification and classification as it is the most important step for image processing. Feature extraction techniques are classified into local (low level) and global (high level) features. Global features such as arch, loop, delta and whorl where as local features such as ridge end and bifurcation called minutiae are majors of automatic fingerprint recognition system. In this study, it has been observed that most of the fingerprint recognition systems are based on minutiae features. In this paper we analyze the various feature extraction methods used so far with their mathematical background to the readers.