Asem A. Othman, (West Virginia University), “Mixing Biometric Data For Generating Joint Identities and Preserving Privacy”, 2013

You are here

Inside Signal Processing Newsletter Home Page

Top Reasons to Join SPS Today!

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”, 2013

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.

SPS on Twitter

  • DEADLINE EXTENDED: The 2023 IEEE International Workshop on Machine Learning for Signal Processing is now accepting… https://t.co/NLH2u19a3y
  • ONE MONTH OUT! We are celebrating the inaugural SPS Day on 2 June, honoring the date the Society was established in… https://t.co/V6Z3wKGK1O
  • The new SPS Scholarship Program welcomes applications from students interested in pursuing signal processing educat… https://t.co/0aYPMDSWDj
  • CALL FOR PAPERS: The IEEE Journal of Selected Topics in Signal Processing is now seeking submissions for a Special… https://t.co/NPCGrSjQbh
  • Test your knowledge of signal processing history with our April trivia! Our 75th anniversary celebration continues:… https://t.co/4xal7voFER

IEEE SPS Educational Resources

IEEE SPS Resource Center

IEEE SPS YouTube Channel