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A Novel Encryption Method for Dorsal Hand Vein Images on a Microcomputer

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submitted on 2024-03-06, 06:35 and posted on 2024-03-06, 06:36 authored by M. Z. Yildiz, O. F. Boyraz, E. Guleryuz, A. Akgul, I. Hussain

In this paper, a Lorenz-like chaotic system was developed to encrypt the dorsal hand patterns on a microcomputer. First, the dorsal hand vein images were taken from the subjects via an infrared camera. These were subjected to two different processes called contrast enhancement and segmentation of vein regions. Second, the pre- and post-processed images were encrypted with a new encryption algorithm in the microcomputer environment. For the encryption process, random numbers were generated by the chaotic system. These random numbers were subjected to NIST-800-22 test which is the most widely accepted statistical test suite. The speeded up robust feature (SURF) matching algorithm was utilized in the initial condition sensitivity analysis of the encrypted images. The results of the analysis have shown that the proposed encryption algorithm can be used in identification and verification systems. The encrypted images were analyzed with histogram, correlation, entropy, pixel change rate (NPCR), initial condition sensitivity, data loss, and noise attacks which are frequently used for security analyses in the literature. In addition, the images were analyzed after noise attacks by means of peak signal-to-noise ratio (PSNR), mean square error (MSE), and the structural similarity index (SSIM) tests. It has been shown that the dorsal hand vein images can be used in identification systems safely with the help of the proposed method on microcomputers.

Other Information

Published in: IEEE Access
License: https://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1109/access.2019.2914721

Funding

Open Access funding provided by the Qatar National Library.

History

Language

  • English

Publisher

IEEE

Publication Year

  • 2019

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License

Institution affiliated with

  • Qatar University
  • College of Arts and Sciences - QU