A CNN approach for the identification of dorsal veins of the hand

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%.