A CNN approach for the identification of dorsal veins of the hand
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Date
2022-01-24
Journal Title
Journal ISSN
Volume Title
Publisher
University of Eloued جامعة الوادي
Abstract
In this paper, we proposed a dorsal hand vein
recognition method based on Convolutional Neural Network
(CNN). Firstly, implementations of raw images the region of
interest (ROI) of dorsal hand vein images was extracted, and
then contrast limited adaptive histogram equalization (CLAHE)
and were used to preprocess the images. Next, the extraction of
information using the Sato filter and the Otsu thresholding
algorithm to create a new database containing only the processed
images. Finally, CNN was applied for identification. The
experimental results was has been optimized with
Hyperparameter Optimization. The dorsal hand vein recognition
rate reaches 99%.
Description
Forum Intervention of Artificial Intelligence and Its Applications. Faculty of Exat science. University of Eloued
Keywords
dorsal hand vein recognition; deep learning; convolutional neural network, CLAHE, SATO, OTSU, mask
Citation
Benaouda, Abdelkarim. Haouari Mustapha, Aymen. Benziane, Sarâh. A CNN approach for the identification of dorsal veins of the hand. Forum of Artificial Intelligence and Its Applications. 24-26 Jan 2022. Faculty of Exat science. University of Eloued. [visited in ../../….]. available from [copy the link here]