The technology we use, and even rely on, in our everyday lives –computers, radios, video, cell phones – is enabled by signal processing. Learn More »
1. IEEE Signal Processing Magazine
2. Signal Processing Digital Library*
3. Inside Signal Processing Newsletter
4. SPS Resource Center
5. Career advancement & recognition
6. Discounts on conferences and publications
7. Professional networking
8. Communities for students, young professionals, and women
9. Volunteer opportunities
10. Coming soon! PDH/CEU credits
Click here to learn more.
News and Resources for Members of the IEEE Signal Processing Society
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.
Nomination/Position | Deadline |
---|---|
Submit Your Papers for ICASSP 2026! | 17 September 2025 |
Call for Nominations: Awards Board, Industry Board and Nominations & Elections Committee | 19 September 2025 |
Meet the 2025 Candidates: IEEE President-Elect | 1 October 2025 |
Call for proposals: 2027 IEEE Conference on Artificial Intelligence (CAI) | 1 October 2025 |
Take Part in the 2025 Low-Resource Audio Codec (LRAC) Challenge | 1 October 2025 |
Call for Nominations for the SPS Chapter of the Year Award | 15 October 2025 |
Call for Papers for 2026 LRAC Workshop | 22 October 2025 |
Submit a Proposal for ICASSP 2030 | 31 October 2025 |
Call for Project Proposals: IEEE SPS SigMA Program - Signal Processing Mentorship Academy | 2 November 2025 |
Home | Sitemap | Contact | Accessibility | Nondiscrimination Policy | IEEE Ethics Reporting | IEEE Privacy Policy | Terms | Feedback
© Copyright 2025 IEEE - All rights reserved. Use of this website signifies your agreement to the IEEE Terms and Conditions.
A public charity, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.