Iris Recognition Based on Human-Interpretable Features | Matlab Image Processing Final Year Project
Iris Recognition Based on Human-Interpretable Features | Matlab Image Processing Final Year IEEE project with source code.
To buy this project in ONLINE, Contact:
Email: [email protected],
Website: https://www.jpinfotech.org
IEEE Base Paper Title: Iris Recognition Based on Human-Interpretable Features.
Implementation: MATLAB.
Cost (In Indian Rupees): Rs.3000/.
IEEE Base paper Abstract:
The iris is a stable biometric trait that has been widely used for human recognition in various applications. However, deployment of iris recognition in forensic applications has not been reported. A primary reason is the lack of human-friendly techniques for iris comparison. To further promote the use of iris recognition in forensics, the similarity between irises should be made visualizable and interpretable. Recently, a human-in-the-loop iris recognition system was developed, based on detecting and matching iris crypts. Building on this frame-work, we propose a new approach for detecting and matching iris crypts automatically. Our detection method is able to capture iris crypts of various sizes. Our matching scheme is designed to handle potential topological changes in the detection of the same crypt in different images. Our approach outperforms the known visible-feature-based iris recognition method on three different data sets. In particular, our approach achieves over 22% higher rank one hit rate in identification, and over 51% lower equal error rate in verification. In addition, the benefit of our approach on multi-enrollment is experimentally demonstrated.
REFERENCE:
Jianxu Chen, Feng Shen, Danny Ziyi Chen, Fellow, IEEE, and Patrick J. Flynn, Fellow, IEEE, “Iris Recognition Based on Human-Interpretable Features”, IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 11, NO. 7, JULY 2016
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