DocumentCode :
1550342
Title :
Analysis of Facial Marks to Distinguish Between Identical Twins
Author :
Srinivas, N. ; Aggarwal, G. ; Flynn, P.J. ; Vorder Bruegge, R.W.
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of Notre Dame, Notre Dame, IN, USA
Volume :
7
Issue :
5
fYear :
2012
Firstpage :
1536
Lastpage :
1550
Abstract :
Identical twin face recognition is a challenging task due to the existence of a high degree of correlation in overall facial appearance. Commercial face recognition systems exhibit poor performance in differentiating between identical twins under practical conditions. In this paper, we study the usability of facial marks as biometric signatures to distinguish between identical twins. We propose a multiscale automatic facial mark detector based on a gradient-based operator known as the fast radial symmetry transform. The transform detects bright or dark regions with high radial symmetry at different scales. Next, the detections are tracked across scales to determine the prominence of facial marks. Extensive experiments are performed both on manually annotated and on automatically detected facial marks to evaluate the usefulness of facial marks as biometric signatures. Experiment results are based on identical twin images acquired at the 2009 Twins Days Festival in Twinsburg, Ohio. The results of our analysis signify the usefulness of the distribution of facial marks as a biometric signature. In addition, our results indicate the existence of some degree of correlation between geometric distribution of facial marks across identical twins.
Keywords :
face recognition; gradient methods; humanities; mathematical operators; transforms; automatically detected facial marks; biometric signatures; bright region detection; dark region detection; face recognition systems; facial appearance; facial marks analysis; fast radial symmetry transform; gradient-based operator; identical twin face recognition; manually annotated facial marks; multiscale automatic facial mark detector; Detectors; Face; Face recognition; Image color analysis; Manuals; Observers; Skin; Face recognition; facial marks; identical twins;
fLanguage :
English
Journal_Title :
Information Forensics and Security, IEEE Transactions on
Publisher :
ieee
ISSN :
1556-6013
Type :
jour
DOI :
10.1109/TIFS.2012.2206027
Filename :
6228529
Link To Document :
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