Latent Fingerprint Matching Using Descriptor-Based Hough Transform

Identifying suspects based on impressions of fingers lifted from crime scenes (latent prints) is a routine procedure that is extremely important to forensics and law enforcement agencies. Latents are partial fingerprints that are usually smudgy, with small area and containing large distortion. Due to these characteristics, latents have a significantly smaller number of minutiae points compared to full (rolled or plain) fingerprints. The small number of minutiae and the noise characteristic of latents make it extremely difficult to automatically match latents to their mated full prints that are stored in law enforcement databases. Although a number of algorithms for matching full-to-full fingerprints have been published in the literature, they do not perform well on the latent-to-full matching problem. Further, they often rely on features that are not easy to extract from poor quality latents. In this paper, we propose a new fingerprint matching algorithm which is especially designed for matching latents. The proposed algorithm uses a robust alignment algorithm (descriptor-based Hough transform) to align fingerprints and measures similarity between fingerprints by considering both minutiae and orientation field information. To be consistent with the common practice in latent matching (i.e., only minutiae are marked by latent examiners), the orientation field is reconstructed from minutiae. Since the proposed algorithm relies only on manually marked minutiae, it can be easily used in law enforcement applications. Experimental results on two different latent databases (NIST SD27 and WVU latent databases) show that the proposed algorithm outperforms two well optimized commercial fingerprint matchers. Further, a fusion of the proposed algorithm and commercial fingerprint matchers leads to improved matching accuracy.

[1]  Anil K. Jain,et al.  Latent fingerprint enhancement via robust orientation field estimation , 2011, 2011 International Joint Conference on Biometrics (IJCB).

[2]  I. Dror,et al.  Contextual information renders experts vulnerable to making erroneous identifications. , 2006, Forensic science international.

[3]  Jufu Feng,et al.  A Robust Fingerprint Matching Approach: Growing and Fusing of Local Structures , 2007, ICB.

[4]  Jie Zhou,et al.  Modeling orientation fields of fingerprints with rational complex functions , 2004, Pattern Recognit..

[5]  Jie Zhou,et al.  Fingerprint recognition by combining global structure and local cues , 2006, IEEE Transactions on Image Processing.

[6]  Barry G. Sherlock,et al.  A model for interpreting fingerprint topology , 1993, Pattern Recognit..

[7]  R. A. Hicklin,et al.  Repeatability and Reproducibility of Decisions by Latent Fingerprint Examiners , 2012, PloS one.

[8]  Anil K. Jain,et al.  Latent Fingerprint Matching: Fusion of Rolled and Plain Fingerprints , 2009, ICB.

[9]  Anil K. Jain,et al.  Latent Fingerprint Matching: Fusion of Manually Marked and Derived Minutiae , 2010, 2010 23rd SIBGRAPI Conference on Graphics, Patterns and Images.

[10]  Xudong Jiang,et al.  Fingerprint Retrieval for Identification , 2006, IEEE Transactions on Information Forensics and Security.

[11]  Pauli Kuosmanen,et al.  Fingerprint Matching Using an Orientation-Based Minutia Descriptor , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Anil K. Jain,et al.  Fingerprint Reconstruction: From Minutiae to Phase , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Axel Munk,et al.  Global Models for the Orientation Field of Fingerprints: An Approach Based on Quadratic Differentials , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[14]  Massimo Tistarelli,et al.  MCC: A baseline algorithm for fingerprint verification in FVC-onGoing , 2010, 2010 11th International Conference on Control Automation Robotics & Vision.

[15]  Jie Zhou,et al.  A Performance Evaluation of Fingerprint Minutia Descriptors , 2011, 2011 International Conference on Hand-Based Biometrics.

[16]  Jianjiang Feng,et al.  Combining minutiae descriptors for fingerprint matching , 2008, Pattern Recognit..

[17]  Xudong Jiang,et al.  Fingerprint minutiae matching based on the local and global structures , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[18]  Anil K. Jain,et al.  Filtering large fingerprint database for latent matching , 2008, 2008 19th International Conference on Pattern Recognition.

[19]  Anil K. Jain,et al.  Latent Fingerprint Matching Using Descriptor-Based Hough Transform , 2011, IEEE Transactions on Information Forensics and Security.

[20]  Xinjian Chen,et al.  A new algorithm for distorted fingerprints matching based on normalized fuzzy similarity measure , 2006, IEEE Trans. Image Process..

[21]  Anil K. Jain,et al.  On matching latent fingerprints , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[22]  Yangsheng Wang,et al.  Fingerprint matching combining the global orientation field with minutia , 2005, Pattern Recognit. Lett..

[23]  Richa Singh,et al.  On matching latent to latent fingerprints , 2011, 2011 International Joint Conference on Biometrics (IJCB).

[24]  Richa Singh,et al.  Simultaneous latent fingerprint recognition , 2011, Appl. Soft Comput..

[25]  V. N. Dvornychenko Evaluation of fusion methods for latent fingerprint matchers , 2012, 2012 5th IAPR International Conference on Biometrics (ICB).

[26]  Anil K. Jain,et al.  A Real-Time Matching System for Large Fingerprint Databases , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  Anil K. Jain,et al.  Latent Fingerprint Matching , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[28]  Anil K. Jain,et al.  On latent fingerprint enhancement , 2010, Defense + Commercial Sensing.

[29]  Davide Maltoni,et al.  Minutia Cylinder-Code: A New Representation and Matching Technique for Fingerprint Recognition , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[30]  R. A. Hicklin,et al.  Accuracy and reliability of forensic latent fingerprint decisions , 2011, Proceedings of the National Academy of Sciences.