Separation of overlapped latent fingerprints (OLFs)

Abstract

Fingerprint images generally contains either a single fingerprint(e.g., rolled images)ora set of non-overlapped finger prints (e.g., slap fingerprints). How ever, there are situations where several fingerprints overlap on top of each other.Such situations are frequently in latent fingerprints lifted from the crime scenes or residue fingerprints are left on fingerprint sensors.Overlapped fingerprints constitute a serious challenge to existing fingerprint recognition algorithms,since these algorithms are designed under the assumptions that fingerprints have been properly segmented.In this thesis,a algorithm is proposed to separate overlapped fingerprints into component or individual fingerprints.The basic idea is to first estimate the orientation filed of the given image with overlapped fingerprints and the separate it into component orientation fields using a constrained relaxation labeling technique.Experimental results are satisfactory which indicate that the algorithm leads to good separation of overlapped fingerprints.