Robust iris recognition using decision fusion and degradation modelling
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Description
This thesis investigates the use of fusion techniques and mathematical modelling to increase the robustness of iris recognition systems against iris image quality degradation, pupil size changes and partial occlusion. The proposed techniques improve recognition accuracy and enhance security. They can be further developed for better iris recognition in less constrained environments that do not require user cooperation. A framework to analyse the consistency of different regions of the iris is also developed. This can be applied to improve recognition systems using partial iris images, and cancelable biometric signatures or biometric based cryptography for privacy protection.
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| ID Code: | 89221 |
|---|---|
| Item Type: | QUT Thesis (PhD) |
| Supervisor: | Chandran, Vinod & Boles, Wageeh |
| Keywords: | Biometrics, Iris recognition, Iris degradations, Obfuscation attacks, Robustness, Consistent bits, Decision fusion, Pupil dilation, Biomechanical model, Iris normalisation |
| Divisions: | Past > QUT Faculties & Divisions > Faculty of Science and Technology Past > QUT Faculties & Divisions > Science & Engineering Faculty Past > Schools > School of Electrical Engineering & Computer Science |
| Institution: | Queensland University of Technology |
| Deposited On: | 14 Dec 2015 06:33 |
| Last Modified: | 08 Sep 2017 14:50 |
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