Iris image reconstruction from binary templates: An efficient probabilistic approach based on genetic algorithms

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Abstract

A binary iriscode is a very compact representation of an iris image. For a long time it was assumed that the iriscode did not contain enough information to allow for the reconstruction of the original iris. The present work proposes a novel probabilistic approach based on genetic algorithms to reconstruct iris images from binary templates and analyzes the similarity between the reconstructed synthetic iris image and the original one. The performance of the reconstruction technique is assessed by empirically estimating the probability of successfully matching the synthesized iris image against its true counterpart using a commercial matcher. The experimental results indicate that the reconstructed images look reasonably realistic. While a human expert may not be easily deceived by them, they can successfully deceive a commercial matcher. Furthermore, since the proposed methodology is able to synthesize multiple iris images from a single iriscode, it has other potential applications including privacy enhancement of iris-based systems. © 2013 Elsevier Inc. All rights reserved.

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APA

Galbally, J., Ross, A., Gomez-Barrero, M., Fierrez, J., & Ortega-Garcia, J. (2013). Iris image reconstruction from binary templates: An efficient probabilistic approach based on genetic algorithms. Computer Vision and Image Understanding, 117(10), 1512–1525. https://doi.org/10.1016/j.cviu.2013.06.003

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