Iris Biometric Authentication System

Iris Biometric Authentication System

Iris biometric authentication system is a common biometric technique that is being embraced rapidly around the world. It has gained a lot of preference due to the ease in using it and also the difficulty of forging it.  The iris biometric authentication scanners operate by illuminating someone’s iris with invisible infrared light hence picking up unique patterns that are not visible to the naked eye and storing this data (Mazumdar, 2018). The two sets of data will later be compared for similarity during the authentication process.

Iris biometric authentication is considered amongst the most secure biometric modality when it comes to the identification and verification of an individual. In comparison to other modalities, Iris Recognition has the lowest incidences of false rejection and false acceptance rate. This is because of its high accuracy in mathematical pattern recognition thus assisting it to distinguish individuals from a distant range.

Iris authentication is also highly secured due to the uniqueness of its patterns. Its ability to scan biometrics from range has also hygiene benefits, unlike retina and fingerprint scanners. The iris patterns are also highly random thus allowing variability of about 244 degrees of freedom and entropy of over 3.2 bits per square millimetre (Menon, 2018). The system is also quick in biometric authentication due to fast encoding time.

Although the Iris authentication has quite a several advantages, there are also a few challenges that face the recognition system. The major challenge facing this system is that it is relatively expensive compared to other biometric modalities. Constant scanning of the Iris by infrared light eventually harms it (Nazmdeh, 2019), because the iris is very small and hence the distance between the eye and the iris-scanning device should be less than a few meters.

References

Mazumdar, J. B., & Nirmala, S. R. (2018). Retina based biometric authentication system: a review. International Journal of Advanced Research in Computer Science, 9(1).

Menon, H., & Mukherjee, A. (2018, May). Iris biometrics using deep convolutional networks. In 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) (pp. 1-5). IEEE.

Nazmdeh, V., Mortazavi, S., Tajeddin, D., Nazmdeh, H., & Asem, M. M. (2019, January). Iris recognition; from classic to modern approaches. In 2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC) (pp. 0981-0988). IEEE.