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Analysis of Facial Marks to Distinguish between Identical Twins

NCJ Number
IEEE Trans. Information Forensics and Security
N. Srinivas; G. Aggarwal; P. Flynn
Date Published
February 2022
0 pages

Since Identical-twin face recognition is a challenging task due to the existence of a high degree of correlation in overall facial appearance and commercial face recognition systems exhibit poor performance in differentiating between identical twins under practical conditions, the current project examined the usability of facial marks as biometric signatures to distinguish between identical twins.


The project used 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 were tracked across scales to determine the prominence of facial marks. Extensive experiments were performed both on manually annotated and on automatically detected facial marks to evaluate the usefulness of facial marks as biometric signatures. Experiment results were based on identical twin images acquired at the 2009 Twins Days Festival in Twinsburg, Ohio. The results of the analysis indicate the usefulness of the distribution of facial marks as a biometric signature. In addition, the results indicate some degree of correlation between geometric distribution of facial marks across identical twins. (publisher abstract modified)

Date Published: February 18, 2022