Real-Time Iris Detection and Recognition System Using You Only Look Once Version 8
Parthasarathy C1, Priscilla Rachel G2, Rachel Sherin J3
1Parthasarathy C, Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai (Tamil Nadu), India.
2Priscilla Rachel G, Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai (Tamil Nadu), India.
3Rachel Sherin J, Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai (Tamil Nadu), India.
Manuscript received on 30 November 2024 | First Revised Manuscript received on 11 December 2024 | Second Revised Manuscript received on 25 January 2025 | Manuscript Accepted on 15 February 2025 | Manuscript published on 28 February 2025 | PP: 13-17 | Volume-12 Issue-2, February 2025 | Retrieval Number: 100.1/ijies.L109611121224 | DOI: 10.35940/ijies.L1096.12020225
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The model which is used in real time object detection which has high speed and accuracy which processes the images in a single pass is the You Look Only Once model. This project mainly the focus on the application of YOLOv8 or You Look Only Once version 8 model for iris detection and recognition in biometric systems, focusing on high-security and accuracy. to improve the performance of model under various lighting conditions it was trained under various customized datasets. To improve the generalization of the model advanced image augmentation techniques like flips, rotation and brightness adjustments were done . The model yielded 95% average precision on the validation set which was trained using pytorch framework with optimized hyperparameters which shows the effectiveness of YOLOv8 in real time iris recognition and detection.
Keywords: Iris Recognition System, Image Augmentation, Pytorch Framework, Hyper Parameter, Generalization.
Scope of the Article: Computer Science and Applications