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Date of Award
2013
Document Type
Thesis - Pacific Access Restricted
Degree Name
Master of Science (M.S.)
Department
Engineering Science
First Advisor
Anahita Zarci
First Committee Member
Louise Stark
Second Committee Member
Ken Hughes
Third Committee Member
Jinzhu Gao
Fourth Committee Member
Jennifer Ross
Abstract
Image categorization is often performed manually, which can be a time consuming and a very difficult process, especially for human iris images. Previous researchers have been working on predicting ethnicity from texture features of iris images using other methods. This thesis is one of the the first to present a solution of iris image categorization using artificial neural networks, specifically for human iris images with discernible and complicated textures. The work will allow users to quickly and automatically categorize human iris images by using supervised and unsupervised learning algorithms. Contributions of this solution include a fast and accurate way to apply iris matching and solve the time consuming problems. The solution aims to find efficient and appropriate artificial neural network algorithms that can categorize iris images based on texture features. Detailed algorithms, specific techniques, performance analysis, limitations and future work will be also provided in this thesis.
Pages
166
Recommended Citation
Mou, Duxing. (2013). Human iris categorization using artificial neural networks. University of the Pacific, Thesis - Pacific Access Restricted. https://scholarlycommons.pacific.edu/uop_etds/856
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