Advancements in Iris Recognition: WAHET-CNN Framework for Accurate Segmentation and Pattern Classification

Authors

DOI:

https://doi.org/10.4108/eetcasa.v9i1.3708

Keywords:

iris recognition, periocular recognition, iris segmentation, iris biometric, personal identification

Abstract

Biometric and identification patterns have gained extensive research and application, particularly in iris recognition. The iris harbors a wealth of individual-specific information, making it a vital element in biometric authentication. This article presents a comprehensive study encompassing iris segmentation and identification. We introduce the Weighted Adaptive Hough Ellipsopolar Transform Convolutional Neural Network (WAHET-CNN) as a novel approach for classifying pattern images. Our experimental outcomes demonstrate a commendable 90% accuracy achieved by the proposed WAHET-CNN on the CASIA dataset Version 4.

References

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Published

14-08-2023

How to Cite

1.
Kim Quoc N, Minh Tan H, Nhu Phu D, Xuan Chi V, Cong Vinh P. Advancements in Iris Recognition: WAHET-CNN Framework for Accurate Segmentation and Pattern Classification. EAI Endorsed Trans Context Aware Syst App [Internet]. 2023 Aug. 14 [cited 2024 Dec. 2];9. Available from: https://publications.eai.eu/index.php/casa/article/view/3708

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