DocumentCode :
23439
Title :
The Individuality of Relatively Permanent Pigmented or Vascular Skin Marks (RPPVSM) in Independently and Uniformly Distributed Patterns
Author :
Nurhudatiana, Arfika ; Kong, Adams Wai-Kin ; Matinpour, K. ; Chon, D. ; Altieri, L. ; Siu-Yeung Cho ; Craft, N.
Author_Institution :
Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore
Volume :
8
Issue :
6
fYear :
2013
fDate :
Jun-13
Firstpage :
998
Lastpage :
1012
Abstract :
With recent advances in multimedia technology, the involvement of digital images/videos in crimes has been increasing significantly. Identification of individuals in these images/videos can be challenging. For example, in cases of child sexual abuse, child pornography, and masked gunmen, the faces of criminals or victims are often hidden or covered and only some body parts (e.g., back, thigh, and arm) can be observed from the digital evidence. Although tattoos and scars can be used for identification in some cases, they are neither universal nor unique. We propose a group of skin marks named Relatively Permanent Pigmented or Vascular Skin Marks (RPPVSM) as a biometric trait for forensic identification. To support the scientific underpinnings of using RPPVSM patterns as a novel biometric trait, the individuality was studied. RPPVSM on the backs of 269 male subjects were examined. We found that RPPVSM in middle to low density patterns tend to form an independent and uniform distribution, while RPPVSM in high density patterns tend to form clusters. We present in this paper an individuality model for the independently and uniformly distributed RPPVSM patterns. When compared to the empirical results, this model fits the empirical distribution very well. Finally, the predicted error rates for verification and identification are reported.
Keywords :
biometrics (access control); image forensics; pattern classification; RPPVSM trait pattern; biometric trait; digital evidence; digital image; digital video; forensic identification; multimedia technology; relatively permanent pigmented skin; vascular skin mark; Back; Biomedical imaging; Distribution functions; Graphical models; Pattern matching; Skin; Videos; Forensics; individuality; predicted error rates; probability of random correspondence; skin marks; statistics;
fLanguage :
English
Journal_Title :
Information Forensics and Security, IEEE Transactions on
Publisher :
ieee
ISSN :
1556-6013
Type :
jour
DOI :
10.1109/TIFS.2013.2258338
Filename :
6502710
Link To Document :
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