• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2420-2433
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• 2014

Fusing the scores of multibiometrics is a very promising approach to improve the overall system's accuracy and the verification performance. In recent years, there are several approaches towards studying score level fusion of several biometric systems. However, most of them does not consider the genuine and imposter score distributions and result in a higher equal error rate usually. In this paper, a novel score level fusion approach of different biometric systems (dual iris, thermal and visible face traits) based on $Acz{\acute{e}}l$-Alsina triangular norm is proposed. It achieves higher identification performance as well as acquires a closer genuine distance and larger imposter distance. The experimental tests are conducted on a virtual multibiometrics database, which merges the challenging CASIA-Iris-Thousand database with noisy samples and the NVIE face database with visible and thermal face images. The rigorous results suggest that significant performance improvement can be achieved after the implementation of multibiometrics. The comparative experiments also ascertain that the proposed fusion approach outperforms the state-of-art verification performance.

• International Journal of Contents
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• v.9 no.2
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• pp.14-21
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• 2013

Current smartphone authentication systems are deemed inconvenient and difficult for users on remembering their password as well as privacy issues on stolen or forged biometrics. New authentication system is demanded to be implicit to users with very minimum user involvement being. This idea aims towards a future model of authentication system for smartphones users without users realizing them being authenticated. We use the most frequent activity that users carry out with their smartphone, which is the calling activity. We derive two basics related interactions that are first factor being arm's flex (AF) action to pick a phone to be near ones' ears and then once getting near ear using second factor from ear shape image. Here, we combine behavior biometrics from AF in first factor and physical biometrics from ear image in second factor. Our study shows our dual-factor authentication system does not require explicit user interaction thereby improving convenience and alleviating burden from users from persistent necessity to remember password. These findings will augment development of novel implicit authentication system being transparent, easier, and unobtrusive for users.