Literature DB >> 21808092

Altered fingerprints: analysis and detection.

Soweon Yoon1, Jianjiang Feng, Anil K Jain.   

Abstract

The widespread deployment of Automated Fingerprint Identification Systems (AFIS) in law enforcement and border control applications has heightened the need for ensuring that these systems are not compromised. While several issues related to fingerprint system security have been investigated, including the use of fake fingerprints for masquerading identity, the problem of fingerprint alteration or obfuscation has received very little attention. Fingerprint obfuscation refers to the deliberate alteration of the fingerprint pattern by an individual for the purpose of masking his identity. Several cases of fingerprint obfuscation have been reported in the press. Fingerprint image quality assessment software (e.g., NFIQ) cannot always detect altered fingerprints since the implicit image quality due to alteration may not change significantly. The main contributions of this paper are: 1) compiling case studies of incidents where individuals were found to have altered their fingerprints for circumventing AFIS, 2) investigating the impact of fingerprint alteration on the accuracy of a commercial fingerprint matcher, 3) classifying the alterations into three major categories and suggesting possible countermeasures, 4) developing a technique to automatically detect altered fingerprints based on analyzing orientation field and minutiae distribution, and 5) evaluating the proposed technique and the NFIQ algorithm on a large database of altered fingerprints provided by a law enforcement agency. Experimental results show the feasibility of the proposed approach in detecting altered fingerprints and highlight the need to further pursue this problem.

Mesh:

Year:  2012        PMID: 21808092     DOI: 10.1109/TPAMI.2011.161

Source DB:  PubMed          Journal:  IEEE Trans Pattern Anal Mach Intell        ISSN: 0098-5589            Impact factor:   6.226


  4 in total

1.  A support vector machine approach for truncated fingerprint image detection from sweeping fingerprint sensors.

Authors:  Chi-Jim Chen; Tun-Wen Pai; Mox Cheng
Journal:  Sensors (Basel)       Date:  2015-03-31       Impact factor: 3.576

2.  The potential of using brain images for authentication.

Authors:  Fanglin Chen; Zongtan Zhou; Hui Shen; Dewen Hu
Journal:  ScientificWorldJournal       Date:  2014-07-10

3.  SVM-based synthetic fingerprint discrimination algorithm and quantitative optimization strategy.

Authors:  Suhang Chen; Sheng Chang; Qijun Huang; Jin He; Hao Wang; Qiangui Huang
Journal:  PLoS One       Date:  2014-10-27       Impact factor: 3.240

4.  Recognizing disguised faces: human and machine evaluation.

Authors:  Tejas Indulal Dhamecha; Richa Singh; Mayank Vatsa; Ajay Kumar
Journal:  PLoS One       Date:  2014-07-16       Impact factor: 3.240

  4 in total

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