Date of Graduation


Document Type


Degree Type



Statler College of Engineering and Mineral Resources


Lane Department of Computer Science and Electrical Engineering

Committee Chair

Arun Ross

Committee Member

Bojan Cukic

Committee Member

Katerina Goseva


Recent research in iris recognition has established the impact of non-cosmetic soft contact lenses on the recognition performance of iris matchers. Researchers in Notre Dame demonstrated an increase in False Reject Rate (FRR) when an iris without a contact lens was compared against the same iris with a transparent soft contact lens. Detecting the presence of a contact lens in ocular images can, therefore, be beneficial to iris recognition systems. This study proposes a method to automatically detect the presence of non-cosmetic soft contact lenses in ocular images of the eye acquired in the Near Infrared (NIR) spectrum. While cosmetic lenses are more easily discernible, the problem of detecting non-cosmetic lenses is substantially difficult and poses a significant challenge to iris researchers. In this work, the lens boundary is detected by traversing a small annular region in the vicinity of the outer boundary of the segmented iris and locating candidate points corresponding to the lens perimeter. Candidate points are identified by examining intensity profiles in the radial direction within the annular region. The proposed detection method is evaluated on two databases: ICE 2005 and MBGC Iris. In the ICE 2005 database, a correct lens detection rate of 72% is achieved with an overall classification accuracy of 76%. In the MBGC Iris database, a correct lens detection rate of 70% is obtained with an overall classification accuracy of 66:8%. To the best of our knowledge, this is one of the earliest work attempting to detect the presence of non-cosmetic soft contact lenses in NIR ocular images.;The second part of this thesis discusses the concept of dual identity, where a digital iris image hosts two distinct identities. In this regard, we design a method to alter a source iris image based on information from a target iris such that the modified iris retains the identity of both images. The proposed model strategically selects a minimal set of pixels from a target identity's iris pattern, copies it onto a source iris pattern, allowing the user to be able to be recognized both as his true identity and as the target identity. Experimental results based on 9506 pairs of source and target images suggest the efficacy of the scheme in rendering a digital iris capable of hosting two distinct identities. This model can potentially be employed to create patterned contact lenses facilitating dual identity by imprinting sparse patterns on transparent contact lenses.