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High-Performance Iris Recognition for Mobile Platforms

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Abstract

In spite of a fact that many standalone iris recognition solutions are successfully implemented and deployed around the world, development of a reliable iris recognition solution capable to provide high recognition performance (both in biometric quality and speed) on mobile device is still an actual task. Main issues related to iris recognition in the mobile devices consist in uncontrollable capturing conditions and limitations in computation power. The aim of the proposed approach is to eliminate aforementioned issues by providing user with comprehensive feedback and, at the same time, performing the most computationally complex operations only on the images of the best quality. Key features of the proposed approach are multi-stage algorithm structure, novel iris image quality estimation and adaptive iris feature vector quantization algorithms. These features allow to achieve high recognition accuracy and real-time performance which are proved by experimental results.

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Authors and Affiliations

  1. Samsung R&D Institute Russia (SRR), Moscow, Russia

    G. A. Odinokikh, A. M. Fartukov, V. A. Eremeev, V. S. Gnatyuk & M. N. Rychagov

  2. Dorodnicyn Computing Centre, Federal Research Center “Computer Science and Control” of RAS, Moscow, 119333, Russia

    G. A. Odinokikh

  3. National Research University of Electronic Technology, Zelenograd, Russia

    M. V. Korobkin

Authors
  1. G. A. Odinokikh
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  2. A. M. Fartukov
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  3. V. A. Eremeev
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  4. V. S. Gnatyuk
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  5. M. V. Korobkin
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  6. M. N. Rychagov
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Corresponding author

Correspondence to G. A. Odinokikh.

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Gleb A. Odinokikh obtained his M.Sc. degree in Bioengineering Systems and Technologies from Bauman Moscow State Technical University. He is currently a Ph.D. student at the Federal Research Center “Informatics and Control,” RAS and research engineer at Samsung R&D Institute Russia. He is the author of several inventions and research works in the field of mobile biometrics, which is the focus of his current research.

Aleksei M. Fartukov received the B.S. and M.S. degrees (with honour) in Computer Science and Engineering in 2002 and the Ph.D. degree in Computer Science and Engineering from National Research University of Electronic Technology (MIET), Moscow, in 2005. Since 2010, he has been research engineer and project leader with Samsung R&D Institute Russia, Moscow. Dr. Fartukov is the author of more than 20 articles and more than 10 inventions. His research interests include image/video processing, compression, and development of biometric systems. Dr. Fartukov participated in the international standardization of new compression algorithms for 3D video coding (MPEG 3D-AVC).

Vladimir A. Eremeev received the M.S. degree (with honour) in applied math from the Moscow Engineering Physics Institute, Moscow, in 1999, and the Ph.D. degree in Physics and Applied Math from the Russian State Hydrometeorologial Institute in 2004. From 1998 to 2007, he was a Research Scientist at the Institute of Ecology and Evolution of the Russian Academy of Sciences. Since 2012, he has been a Research Engineer in the Advanced Media Solutions Team of the Samsung R&D Institute Russia. He is the author of more than 20 articles and 4 inventions. His research interests include image/video processing, computer vision, and machine learning. Dr. Eremeev was a recipient of the Best Young Scientist Award by the Russian Science Support Foundation in 2005.

Vitalii S. Gnatyuk was born in Petropavlovsk-Kamchatskii, Russia, in 1992. He received the M.S. in applied mathematics from Bauman Moscow State Technical University, Moscow, in 2015. Since 2013 he has been a research software engineer in the Advanced Media Solutions Team of the Samsung R&D Institute Russia. He is the author of 4 articles and 2 inventions. His research interests include biometrics, machine learning, and augmented reality. Vitalii Gnatyuk is an awardee of mathematical olympiads of the top Russian technical universities, such as Bauman Moscow State University, the Moscow Engineering Physics Institute, and the Moscow Institute of Physics and Technology. In 2017 he received a Samsung award for the best invention of the year.

Mikhail V. Korobkin received the B.S. and M.S. degrees (with honours) in Computer Science and Engineering from the National Research University of Electronic Technology (MIET), Moscow, in 2013, where he is currently a candidate for the Ph.D. degree. Mr. Korobkin is the author of more than 10 articles and 4 inventions. His research interests include computer vision, machine learning, robotics, and automation.

Mikhail N. Rychagov, Dr.Sc. received the M.S. degree (with honour) in physics from the Department of Physics at Moscow State University, Russia, in 1986. He received the Ph.D. and Dr.Sc. degrees from Moscow State University, Russia, in 1989 and 2000. Since 1989, he has been at the National Research University of Electronic Technology (MIET): associate professor in the Department of Theoretical and Experimental Physics (1998), professor in the Department of Biomedical Systems (2008), and professor in the Department of Informatics and SW for Computer Systems (2014). Since 2004, Dr.Sc. Rychagov has been Director of Department in Samsung R&D Institute Russia, Moscow. His research interests include image and video signal processing, biomedical visualization, biometric technologies, engineering applications of machine learning and artificial intelligence. Dr.Sc. Rychagov is a member of IS&T and IEEE Societies.

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Odinokikh, G.A., Fartukov, A.M., Eremeev, V.A. et al. High-Performance Iris Recognition for Mobile Platforms. Pattern Recognit. Image Anal. 28, 516–524 (2018). https://doi.org/10.1134/S105466181803015X

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