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Protection of Sparse Retinal Templates using Cohort-based Dissimilarity Vectors
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  • Mahshid Sadeghpour ,
  • Arathi Arakala ,
  • Stephen Davis ,
  • Kathy Horadam
Mahshid Sadeghpour
RMIT University

Corresponding Author:[email protected]

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Arathi Arakala
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Stephen Davis
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Kathy Horadam
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In biometric systems, a user’s template may be represented as a vector of dissimilarities from a cohort. This vector can be considered as a pseudonymous identifier in a template protection scheme. We show that for retinal graph templates, which are sparse and so lack regularity, the cohort-based representation achieves three key necessities for the template protection scheme proposed here. First, it has comparable accuracy to an unprotected scheme. Second, it is resistant to an effective inverse method that reconstructs biometric samples from comparison scores. Third, based on the “general framework for evaluating unlinkability” it has local and global linkability scores that are at least as low as well-known state-of-the-art template protection schemes. Our work demonstrates that when a retina is represented using a sparse template, it can be protected using the cohort-based representation.
Apr 2023Published in IEEE Transactions on Biometrics, Behavior, and Identity Science volume 5 issue 2 on pages 233-243. 10.1109/TBIOM.2023.3239866