Abstract:
This research presents a forensics application of matching two latent fingerprints. In crime scene settings, it is often required to match multiple latent fingerprints. U...Show MoreMetadata
Abstract:
This research presents a forensics application of matching two latent fingerprints. In crime scene settings, it is often required to match multiple latent fingerprints. Unlike matching latent with inked or live fingerprints, this research problem is very challenging and requires proper analysis and attention. The contribution of this paper is three fold: (i) a comparative analysis of existing algorithms is presented for this application, (ii) fusion and context switching frameworks are presented to improve the identification performance, and (Hi) a multi-latent fingerprint database is prepared. The experiments highlight the need for improved feature extraction and processing methods and exhibit large scope of improvement in this important research problem.
Published in: 2011 International Joint Conference on Biometrics (IJCB)
Date of Conference: 11-13 October 2011
Date Added to IEEE Xplore: 29 December 2011
ISBN Information:
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1.
http://fingerprint . nist . gov/standard/cdeffs/index.html.
2.
NBIS (NIST biometric image software). Developed by National Institute of Standards and Technology http://www.nist.gov/itl/iad/ig/nbis.cfm.
3.
Neurotechnology veri fnger. www.neurotechnology . com/verifinger.html.
4.
NIST special database 27. Fingerprint Minu-tiae from Latent and Matching Tenprint Images http://www.nist.gov/srd/nistsd27.htm.
5.
V. Dvornychenko and M. Garris. Summary of NIST latent fingerprint testing workshop. Technical Report NISTIR 7377,2006.
6.
J. Feng and A. K. Jain. Filtering large fingerprint database for latent matching. In Proceedings of International Conference on Pattern Recognition, pages 1-4, 2008.
7.
M. Hearst, S. Dumais, E. Osman, J. Platt, and B. Scholkopf Support vector machines. IEEE Intelligent Systems and their Applications, 13(4):18-28, 1998.
8.
A. Jain and J. Feng. Latent fingerprint matching. IEEE Transactions on PAMI, 33(1):88-100, 2011.
9.
A. K. Jain, J. Feng, A. Nagar, and K. Nandakumar. On matching latent fingerprints. In Proceedings of Computer Vision and Pattern Recognition Workshop, pages 1-8, 2008.
10.
A. K. Jain, A. Nagar, and K. Nandakumar. Latent fingerprint matching. Technical Report MSU-CSE-07-203, Michigan State University, 2007.
11.
A. K. Jain, S. Prabhakar, L. Hong, and S. Pankanti. Finger-code: A filterbank for fingerprint representation and match ing. In Proceedings of Computer Vision and Pattern Recog nition, volume 2, pages 187-193, 1999.
12.
D. Maltoni, D. Maio, A. K. Jain, and S. Prabhakar. Hand book of Fingerprint Recognition. Springer-Verlag, 2003.
13.
K. Moses. Automatic fingerprint identification systems (afis). In Fingerprint Sourcebook, In-ternational Association for Identification. National Institute of Justice, Washington DC, 2009. http://www.ncjrs.gov/pdffilesl/nij/ 225326.pdf
14.
K. Nandakumar, Y. Chen, S. Dass, and A.K.Jain. Likelihood ratio based biometric score fusion. IEEE Transactions on PAMI, 30(2):342-347, 2008.
15.
L. Rosa. Filterbank-based fingerprint matching. http://www. advancedsourcecode.com.
16.
A. Ross, K. Nandakumar, and A. Jain. Springer, 2006.
17.
M. Vatsa, R. Singh, A. Noore, and K. Morris. Simultaneous latent fingerprint recognition: A preliminary study. In Proceedings of Biometrics: Theory, Applications, and Systems, pages 1-5,2009.
18.
M. Vatsa, R. Singh, A. Noore, and A. Ross. On the dynamic selection of biometric fusion algorithms. IEEE Transactions on IFS, 5(3):470-479, 2010.
19.
S. Yoon, J. Feng, and A. K. Jain. On latent fingerprint enhancement. In Proceedings of SPIE Biometric Technology for Human Identification, 2010.
20.
Q. Zhao, J. Feng, and A. K. Jain. Latent fingerprint matching: Utility of level 3 features. Technical Report MSU-CSE-10-14, Michigan State University, August 2010.