Dorsal Hand Vein Identification Based on Binary Particle Swarm Optimization

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.

Advances in Algorithm, Multimedia, and Network for Future IT

“…Benziane and Benyettou [5] propose a decision support system that gets an electronic signature from hand for the purpose of identification/authentication. In order to fulfill objectives, a complete image pre-processing chain, which consists of ROI extraction, grayscale normalization, an anisotropic diffusion filter, and contrast-limited adaptive histogram equalization, is proposed.…”