The rapid advance of information technology has allowed for a rise in the use of biometric markers to automatically track the identity of individuals. Iris biometrics has emerged as one of the most reliable and accurate systems when dealing with cooperating subjects, however, challenges arise when attempting to minimize the amount of intrusion when examining subjects. Allowing for more flexibility in data capture settings will introduce differences in the iris texture due to changes in ambient light, which may negatively impact recognition results. This research examines the feasibility of using 3D software to synthetically dilate the pupils of existing iris images to more closely match the size of a target image. Methods are developed first to evaluate the compatibility of synthetic images with iris identification software, and then to examine what specific areas of the iris texture differ between synthetic and real images. Results show synthetic images are found to be compatible with the recognition process and have the potential to improve performance.
","abstract_html":"<p>The rapid advance of information technology has allowed for a rise in the use of biometric markers to automatically track the identity of individuals. Iris biometrics has emerged as one of the most reliable and accurate systems when dealing with cooperating subjects, however, challenges arise when attempting to minimize the amount of intrusion when examining subjects. Allowing for more flexibility in data capture settings will introduce differences in the iris texture due to changes in ambient light, which may negatively impact recognition results. This research examines the feasibility of using 3D software to synthetically dilate the pupils of existing iris images to more closely match the size of a target image. Methods are developed first to evaluate the compatibility of synthetic images with iris identification software, and then to examine what specific areas of the iris texture differ between synthetic and real images. Results show synthetic images are found to be compatible with the recognition process and have the potential to improve performance.</p>","abstract_has_math":false,"creators":["Hasegawa, Robert Shigehisa"],"institution":null,"degree_name":"Master of Science (M.S.)","degree_level":"Thesis - Pacific Access Restricted","degree_discipline":"Engineering Science","degree_department":null,"school":null,"contributors":["Ken Hughes"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012-01-01T08:00:00Z","date_published":"2012-01-01T08:00:00Z","updated_at":"2026-07-24T05:36:52Z","subjects":["Biometric identification","Biometric analysis","Iris","Eye","Pattern recognition system","Engineering","Physical Sciences and Mathematics"],"languages":[],"rights":[],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://scholarlycommons.pacific.edu/uop_etds/827","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Ken Hughes"]},{"key":"dc:creator","label":"Author","values":["Hasegawa, Robert Shigehisa"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2018-06-29T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Engineering Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - Pacific Access Restricted"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (M.S.)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Biometric identification","Biometric analysis","Iris","Eye","Pattern recognition system","Engineering","Physical Sciences and Mathematics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarlycommons.pacific.edu/uop_etds/827"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The rapid advance of information technology has allowed for a rise in the use of biometric markers to automatically track the identity of individuals. Iris biometrics has emerged as one of the most reliable and accurate systems when dealing with cooperating subjects, however, challenges arise when attempting to minimize the amount of intrusion when examining subjects. Allowing for more flexibility in data capture settings will introduce differences in the iris texture due to changes in ambient light, which may negatively impact recognition results. This research examines the feasibility of using 3D software to synthetically dilate the pupils of existing iris images to more closely match the size of a target image. Methods are developed first to evaluate the compatibility of synthetic images with iris identification software, and then to examine what specific areas of the iris texture differ between synthetic and real images. Results show synthetic images are found to be compatible with the recognition process and have the potential to improve performance.
"]},{"key":"dc:source","label":"Dc Source","values":["88"]},{"key":"dc:title","label":"Title","values":["Using synthetic images to improve iris biometric performance"]}]}],"canonical_facts":{"dc:contributor":["Ken Hughes"],"dc:creator":["Hasegawa, Robert Shigehisa"],"dc:date.available":["2018-06-29T07:00:00Z"],"dc:description.abstract":["The rapid advance of information technology has allowed for a rise in the use of biometric markers to automatically track the identity of individuals. Iris biometrics has emerged as one of the most reliable and accurate systems when dealing with cooperating subjects, however, challenges arise when attempting to minimize the amount of intrusion when examining subjects. Allowing for more flexibility in data capture settings will introduce differences in the iris texture due to changes in ambient light, which may negatively impact recognition results. This research examines the feasibility of using 3D software to synthetically dilate the pupils of existing iris images to more closely match the size of a target image. Methods are developed first to evaluate the compatibility of synthetic images with iris identification software, and then to examine what specific areas of the iris texture differ between synthetic and real images. Results show synthetic images are found to be compatible with the recognition process and have the potential to improve performance.
"],"dc:identifier":["https://scholarlycommons.pacific.edu/uop_etds/827"],"dc:rights":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:source":["88"],"dc:subject":["Biometric identification","Biometric analysis","Iris","Eye","Pattern recognition system","Engineering","Physical Sciences and Mathematics"],"dc:title":["Using synthetic images to improve iris biometric performance"],"thesis:degree_discipline":["Engineering Science"],"thesis:degree_level":["Thesis - Pacific Access Restricted"],"thesis:degree_name":["Master of Science (M.S.)"]},"updated_at":"2026-07-24T05:36:52Z"}