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Updating the Biometric Template by Assessing the Quality of the Original Data

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Abstract

Biometric features used in recognition systems are subject to aging. In addition, there may be variations in working conditions that are not taken into account when registering a user. Therefore, one of the tasks that must be solved when building a universal and long-term functioning biometric system is updating the biometric template. An algorithm for updating a biometric template is proposed that uses an estimate of the distance from the presented biometric features to the user’s features registered under ideal conditions. Such an estimate is calculated by a neural network trained on a database with a large variability in registration conditions. The algorithm is tested on a face recognition system.

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Funding

This work was supported by the Russian Science Foundation, grant no. 20-01-00609.

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Authors and Affiliations

  1. Moscow Institute of Physics and Technology, 141701, Dolgoprudny, Moscow Region, Russia

    I. A. Solomatin & S. B. Kubentaeva

  2. Samsung R&D Institute Russia, Moscow, Russia

    I. A. Solomatin & S. B. Kubentaeva

  3. Federal Research Center “Computer Science and Control,” Russian Academy of Sciences, 119333, Moscow, Russia

    I. A. Matveev

Authors
  1. I. A. Solomatin
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  2. I. A. Matveev
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  3. S. B. Kubentaeva
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Correspondence to I. A. Solomatin or I. A. Matveev.

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The authors declare that they have no conflicts of interest.

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Solomatin, I.A., Matveev, I.A. & Kubentaeva, S.B. Updating the Biometric Template by Assessing the Quality of the Original Data. J. Comput. Syst. Sci. Int. 61, 413–420 (2022). https://doi.org/10.1134/S106423072203008X

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  • DOI: https://doi.org/10.1134/S106423072203008X

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