Real-Time Iris Detection and Recognition System Using You Only Look Once Version 8

: 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.

Authors

Publication Details

Journal
International Journal of Inventive Engineering and Sciences
Published
2025-02-20
DOI
https://doi.org/10.35940/ijies.l1096.12020225
Primary Topic
Biometric Identification and Security
Type
article
Field-Weighted Citation Impact
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article

Real-Time Iris Detection and Recognition System Using You Only Look Once Version 8

C. Parthasarathy, Priscilla Rachel G
International Journal of Inventive Engineering and Sciences
Biometric Identification and Security
article

Real-Time Iris Detection and Recognition System Using You Only Look Once Version 8

C. Parthasarathy, Priscilla Rachel G
article en

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.

International Journal of Inventive Engineering and SciencesVol. 12(2)
Openalex Percentile: Top 97%
Biometric Identification and Security
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Real-Time Iris Detection and Recognition System Using You Only Look Once Version 8 — C. Parthasarathy, Priscilla Rachel G · International Journal of Inventive Engineering and Sciences (2025) | TGRS Research Map | TGRS