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Proceedings Paper

Securing palmprint authentication systems using spoof detection approach
Author(s): Vivek Kanhangad; Abhishek Kumar
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Paper Abstract

Automated human authentication using features extracted from palmprint images has been studied extensively in the literature. Primary focus of the studies thus far has been the improvement of matching performance. As more biometric systems get deployed for wide range of applications, the threat of impostor attacks on these systems is on the rise. The most common among various types of attacks is the sensor level spoof attack using fake hands created using different materials. This paper investigates an approach for securing palmprint based biometric systems against spoof attacks that use photographs of the human hand for circumventing the system. The approach is based on the analysis of local texture patterns of acquired palmprint images for extracting discriminatory features. A trained binary classifier utilizes the discriminating information to determine if the input image is of real hand or a fake one. Experimental results, using 611 palmprint images corresponding to 100 subjects in the publicly available IITD palmprint image database, show that 1) palmprint authentication systems are highly vulnerable to spoof attacks and 2) the proposed spoof detection approach is effective for discriminating between real and fake image samples. In particular, the proposed approach achieves the best classification accuracy of 97.35%.

Paper Details

Date Published: 24 December 2013
PDF: 5 pages
Proc. SPIE 9067, Sixth International Conference on Machine Vision (ICMV 2013), 90671M (24 December 2013); doi: 10.1117/12.2051724
Show Author Affiliations
Vivek Kanhangad, Indian Institute of Technology Indore (India)
Abhishek Kumar, Indian Institute of Technology Indore (India)


Published in SPIE Proceedings Vol. 9067:
Sixth International Conference on Machine Vision (ICMV 2013)
Branislav Vuksanovic; Jianhong Zhou; Antanas Verikas, Editor(s)

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