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Asem A. Othman, (West Virginia University), “Mixing Biometric Data For Generating Joint Identities and Preserving Privacy”, Advisor: Prof. Arun A. Ross, 2013
Biometrics is the science of automatically recognizing individuals by utilizing biological traits such as fingerprints, face, iris and voice. A classical biometric system digitizes the human body and uses this digitized identity for human recognition. In this work, the author introduced the concept of mixing biometrics. Mixing biometrics refers to the process of generating a new biometric image by fusing images of different fingers, different faces, or different irises. The resultant mixed image can be used directly in the feature extraction and matching stages of an existing biometric system. In this regard, the author designed and systematically evaluated novel methods for generating mixed images for the fingerprint, iris and face modalities. Further, the author extended the concept of mixing to accommodate two distinct modalities of an individual, viz., fingerprint and iris. The utility of mixing biometrics was demonstrated in two different applications. The first application deal with the issue of generating a joint digital identity. A joint identity inherits its uniqueness from two or more individuals and can be used in scenarios such as joint bank accounts or two-man rule systems. The second application deal with the issue of biometric privacy, where the concept of mixing was used for de-identifying or obscuring biometric images and for generating cancelable biometrics. Extensive experimental analysis suggested that the concept of biometric mixing has several benefits and can be easily incorporated into existing biometric systems.
For details, please contact the author or visit the thesis page.
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