Dorsal Hand Vein Identification Based on Binary Particle Swarm Optimization


Sarah Hachemi Benziane, Abdelkader Benyettou, Journal of Information Processing Systems Vol. 13, No. 2, pp. 268-283, Apr. 2017  

https://doi.org/10.3745/JIPS.03.0066
Keywords: biometrics, BPSO, GPU, Hand Vein, identification, OTSU
Fulltext:

Abstract

The dorsal hand vein biometric system developed has a main objective and specific targets; to get an electronic signature using a secure signature device. In this paper, we present our signature device with its different aims; respectively: The extraction of the dorsal veins from the images that were acquired through an infrared device. For each identification, we need the representation of the veins in the form of shape descriptors, which are invariant to translation, rotation and scaling; this extracted descriptor vector is the input of the matching step. The optimization decision system settings match the choice of threshold that allows accepting/rejecting a person, and selection of the most relevant descriptors, to minimize both FAR and FRR errors. The final decision for identification based descriptors selected by the PSO hybrid binary give a FAR =0% and FRR=0% as results.


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Cite this article
[APA Style]
Benziane, S. & Benyettou, A. (2017). Dorsal Hand Vein Identification Based on Binary Particle Swarm Optimization. Journal of Information Processing Systems, 13(2), 268-283. DOI: 10.3745/JIPS.03.0066.

[IEEE Style]
S. H. Benziane and A. Benyettou, "Dorsal Hand Vein Identification Based on Binary Particle Swarm Optimization," Journal of Information Processing Systems, vol. 13, no. 2, pp. 268-283, 2017. DOI: 10.3745/JIPS.03.0066.

[ACM Style]
Sarah Hachemi Benziane and Abdelkader Benyettou. 2017. Dorsal Hand Vein Identification Based on Binary Particle Swarm Optimization. Journal of Information Processing Systems, 13, 2, (2017), 268-283. DOI: 10.3745/JIPS.03.0066.