Human Iris Authentication for Autonomous Vehicle

International Journal of Electronics and Communication Engineering

© 2017 by SSRG - IJECE Journal

Volume 4 Issue 5

Year of Publication : 2017

Authors : Saranya M and Sundaresan S.

10.14445/23488549/IJECE-V4I5P104

How to Cite?

Saranya M and Sundaresan S., "Human Iris Authentication for Autonomous Vehicle," SSRG International Journal of Electronics and Communication Engineering, vol. 4,  no. 5, pp. 12-14, 2017. Crossref, https://doi.org/10.14445/23488549/IJECE-V4I5P104

Abstract:

Security has been playing a key role in many places like offices, institutions, libraries, laboratories etc. in order to keep our information confidentially so that no unauthorized person could have an access on them. In modern era, security system doesn’t stops with information alone but has extended to all fields of application viz., autonomous vehicles, machine authentication, automatic door system, etc. Finger print authentication and RFID are not used widely because they are still related to criminal identification. To overcome all the issues, this paper presents a design and implementation of a biometricallycontrolled vehicle ignition system using iris recognition. Black iris is unique for every human and it can’t be duplicated. Hence it is more efficient and reliable for authentication purpose. For providing perfect security and reliability this project takes help of three different technologies viz. embedded system, biometrics and image processing. Iris is sensed by sensor and is validated through image processing algorithms for authentication and the vehicle ignition is provided only for the authorized person.

Keywords:

SFTA, SVM, Curve Operator, IRIS, Anisotropic filter, Canny edge.

References:

[1] Patil, Amol M., Dilip S. Patil, and Pravin S. Patil. "Iris Recognition using Gray Level Co-occurrence Matrix and Hausdorff Dimension." performance evaluation 133.8 (2016).
[2] Vanthana, P. Steffi, and A. Muthukumar. "Iris authentication using Gray Level Co-occurrence Matrix and Hausdorff Dimension." Computer Communication and Informatics (ICCCI), 2015 International Conference on. IEEE, 2015.
[3] Badgandi, Mayank M., and K. Srinivas Rao. "Personal Authentication Based on IRIS Recognition."
[4] Cano, Esteban, et al. "Comparison of Small Unmanned Aerial Vehicles Performance Using Image Processing." Journal of Imaging 3.1 (2017): 4.
[5] Koteswari, S., and P. John Paul. "A Survey: Fusion of Fingerprint and Iris for ATM services." (2017).
[6] Bowyer, Kevin W., and Patrick J. Flynn. "The ND-IRIS- 0405 iris image dataset." arXiv preprint arXiv:1606.04853 (2016).
[7] Sadkhan, Eng Sattar B., Baheeja K. Al-Shukur, and Ali K. Mattar. "Survey of biometrie based key generation to enhance security of cryptosystems." Multidisciplinary in IT and Communication Science and Applications (AIC-MITCSA), Al-Sadeq International Conference on. IEEE, 2016.
[8] Castillo-Carrión, Sebastián, and José-Emilio Guerrero-Ginel. "SIFT optimization and automation for matching images from multiple temporal sources." International Journal of Applied Earth Observation and Geoinformation 57 (2017): 113-122.
[9] Umer, Saiyed, Bibhas Chandra Dhara, and Bhabatosh Chanda. "An Iris Recognition System Based on Analysis of Textural Edgeness Descriptors." IETE Technical Review (2017): 1-12.
[10] He, Fei, et al. "Deep learning architecture for iris recognition based on optimal Gabor filters and deep belief network." Journal of Electronic Imaging 26.2 (2017): 023005-023005.
[11] Barbosa, Jocelyn, et al. "Efficient quantitative assessment of facial paralysis using iris segmentation and active contourbased key points detection with hybrid classifier." BMC medical imaging 16.1 (2016): 23.
[12] Rathgeb, Christian, et al. "Design decisions for an iris recognition sdk." Handbook of Iris Recognition. Springer London, 2016. 359-396.
[13] Alonso-Fernandez, Fernando, Reuben A. Farrugia, and Josef Bigun. "Very low-resolution iris recognition via Eigen-patch super-resolution and matcher fusion." BiometricsTheory, Applications and Systems (BTAS), 2016 IEEE 8th International Conference on. IEEE, 2016.
[14] Alonso-Fernandez, Fernando, Reuben A. Farrugia, and Josef Bigun. "Very low-resolution iris recognition via Eigen-patch super-resolution and matcher fusion." Biometrics Theory, Applications and Systems (BTAS), 2016 IEEE 8th International Conference on. IEEE, 2016.
[15] Tankasala, aSriram Pavan, et al. "Ocular surface vasculature recognition using curvelet transform." IET Biometrics (2016).