کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
527765 869355 2013 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Iris image reconstruction from binary templates: An efficient probabilistic approach based on genetic algorithms
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Iris image reconstruction from binary templates: An efficient probabilistic approach based on genetic algorithms
چکیده انگلیسی


• A novel approach to reconstruct iris images from their iriscodes is presented.
• It is demonstrated the feasibility of such a reverse engineering process.
• Different iris images with very similar iriscodes are produced.
• Commercial systems and human examiners are deceived by the reconstructed images.
• The approach is evaluated following a consistent and reproducible protocol.

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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Vision and Image Understanding - Volume 117, Issue 10, October 2013, Pages 1512–1525
نویسندگان
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