ABC: A Deep learning Iris Recogniser for Secure Borders and Automated Border Crossing

Security is the primary objective for everyone who merits it. Biometric verification is a significant part of banking, societal, and law prosecution security systems. It is essential to have a robust biometric safety system to eradicate disorders and chaos. The automated Border Crossing (ABC) system helps in future border crossing in airports, border check posts, harbor checking points, etc., resulting in congestion control due to a more significant number of passengers. The Automated Border Crossing system can be implemented with various modalities such as iris recognition, fingerprint scan, and face recognition. In the proposed work, iris recognition has been used for person verification for ABC. The system was implemented with the pre-collected data set. The system can be considered as a future up-gradation, a substitute for the passport. The proposed system uses Fast R-CNN on the HAAR CASCADE classifier for iris recognition. With the highest accuracy of 97%, the method proves efficient compared to the existing algorithms with an accuracy of 95%.