Smart Biometrics for Digital India

smart biometrics

Cameras are becoming ubiquitous and the use of biometrics to improve security is ever growing. We propose a method for multi-factor biometric verification mechanism. Our approach is targeted to work on resource constrained devices equipped with a commodity low-resolution monocular camera such as mobiles, tablets, smart TVs and laptops. Our solution is built upon (a) Iris based verification, (b) Periocular features (c) Fingerprint Verification (d) Face verification (e) Liveness Detection. Our process is lightweight, robust and non-intrusive making it ideal for deployment across various platforms equipped with a visible spectrum monocular camera, making it practicable for real-life applications.

Related Publications

  • Ahuja, K., Islam, R., Barbhuiya, F.A. and Dey, K., 2017. Convolutional neural networks for ocular smartphone-based biometrics. Pattern Recognition Letters, 91, pp.17-26.
  • Dwivedi, U., Ahuja, K., Islam, R., Barbhuiya, F.A., Nagar, S. and Dey, K., 2017, March. EyamKayo: Interactive Gaze and Facial Expression Captcha. In Proceedings of the 22nd International Conference on Intelligent User Interfaces Companion (pp. 53-56). ACM.
  • Ahuja, K., Islam, R., Barbhuiya, F.A. and Dey, K., 2016, December. A preliminary study of CNNs for iris and periocular verification in the visible spectrum. In Pattern Recognition (ICPR), 2016 23rd International Conference on (pp. 181-186). IEEE.
  • Islam, R., Ahuja, K., Karmakar, S. and Barbhuiya, F., 2016. Sention: A framework for sensing facial expressions. arXiv preprint arXiv:1608.04489.
  • Ahuja, K., Bose, A., Nagar, S., Dey, K. and Barbhuiya, F., 2016, September. ISURE: User authentication in mobile devices using ocular biometrics in visible spectrum. In Image Processing (ICIP), 2016 IEEE International Conference on(pp. 335-339). IEEE.