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Meam, Limhourlaurent. Iris image segmentation for personal identification using unit gradient vectors and Iris-SAM. Master's Degree(Artificial Intelligence and Internet of Things). Thammasat University. Thammasat University Library. : Thammasat University, 2024.
Iris image segmentation for personal identification using unit gradient vectors and Iris-SAM
Name: Meam, Limhourlaurent
keyword:
Iris recognition
;
Iris-SAM
Abstract:
Iris recognition is one of a fundamental component of computer vision, extensively employed for authentication and identification within security and forensic contexts. Despite its broad utilization, the efficacy of current iris recognition systems is notably compromised under challenging conditions such as suboptimal lighting, partial iris visibility, and eye mis- alignment. These adverse circumstances frequently undermine the reliability of traditional iris recognition methodologies. Central to the effectiveness of iris recognition is the process of iris segmentation, which aims to precisely isolate the iriss annular region from ocular images. Yet, the perfor- mance of conventional iris segmentation techniques typically deteriorates in diverse imaging environments. This thesis introduces an advanced approach to iris segmentation that inte- grates Unit Gradient Vectors (UGVs) with the Iris-Segment Anything Model (Iris-SAM) to enhance segmentation accuracy. This innovative methodology synergistically combines the Daugman algorithm with active contour methods, meticulously optimized using UGVs, to facilitate highly accurate initial segmentation. Further refinement is achieved through the implementation of Iris-SAM, which incorporates Focal Loss to address the significant class imbalance between iris and non-iris regions effectively. Comprehensive empirical evaluations conducted on the CASIA-Iris-Interval-v3 dataset affirm the superiority of this approach. The proposed model attains an average segmentation accuracy of 97.86%, surpassing the Iris-SAM benchmark of 96.94%. This improvement underscores the potential of combining traditional algorithms with modern machine learning techniques to overcome existing limitations and enhance the precision and robustness of iris recognition systems.
Thammasat University. Thammasat University Library
Address:
BANGKOK
Email:
preserv@tu.ac.th
Name: Waree Kongprawechnon
Role:
advisor
Created:
2024
Modified:
2568-05-15
Issued:
2025-04-21
วิทยานิพนธ์/Thesis
application/pdf
eng
DegreeName: Master of Engineering
Level: Master's Degree
Descipline: Artificial Intelligence and Internet of Things
Grantor: Thammasat University
©copyrights Thammasat University
RightsAccess:
ใช้เวลา
0.028556 วินาที
Meam, Limhourlaurent
| Title | Contributor | Type |
|---|---|---|
| Iris image segmentation for personal identification using unit gradient vectors and Iris-SAM
มหาวิทยาลัยธรรมศาสตร์ Meam, Limhourlaurent | Waree Kongprawechnon | วิทยานิพนธ์/Thesis |
Waree Kongprawechnon