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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
On matching latent fingerprints
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
Anil K. Jain, Department of Computer Science and Engineering, Michigan State University, East Lansing, 48824, U.S.A.
Jianjiang Feng, Department of Computer Science and Engineering, Michigan State University, East Lansing, 48824, U.S.A.
Abhishek Nagar, Department of Computer Science and Engineering, Michigan State University, East Lansing, 48824, U.S.A.
Karthik Nandakumar, Institute for Infocomm Research, A*STAR, Fusionopolis, Singapore
Latent fingerprint identification is of critical importance to law enforcement agencies in forensics application. While tremendous progress has been made in the field of automatic fingerprint matching, latent fingerprint matching continues to be a difficult problem because the challenges involved in latent print matching are quite different from plain or rolled fingerprint matching. Poor quality of friction ridge impressions, small finger area and large non-linear distortion are some of the main difficulties in latent fingerprint matching. We propose a system for matching latent images to rolled fingerprints that takes into account the specific characteristics of the latent matching problem. In addition to minutiae, additional features like orientation field and quality map are also used in our system. Experimental results on the NIST SD27 latent database indicate that the introduction of orientation field and quality map to minutiae-based matching leads to good recognition performance despite the inherently difficult nature of the problem. We achieve the rank-20 accuracy of 93.4% in retrieving 258 latents from a background database of 2,258 rolled fingerprints.
Citation:
Anil K. Jain, Jianjiang Feng, Abhishek Nagar, Karthik Nandakumar, "On matching latent fingerprints," cvprw, pp.1-8, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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