Venipuncture is the most common way of all invasive medical procedures. A vein display system can make vein access
easier by capturing the vein information and projecting a visible vein image onto the skin, which is correctly aligned with
the subject’s vein. The existing systems achieve correct alignment by the design of coaxial structure. Such a structure
causes complex optical and mechanical design and big physical dimensions inevitably. In this paper, we design a stereovision-
based vein display system, which consists of a pair of cameras, a DLP projector and a near-infrared light source.
We recover the three-dimensional venous structure from image pair acquired from two near-infrared cameras. Then the
vein image from the viewpoint of projector is generated from the three-dimensional venous structure and projected
exactly onto skin by the DLP projector. Since the stereo cameras get the depth information of vessels, the system can
make sure the alignment of projected veins and the real veins without a coaxial structure. The experiment results prove
that we propose a feasible solution for a portable and low-cost vein display device.
Subcutaneous vein images are often obtained by using the absorbency difference of near-infrared (NIR) light between vein and its surrounding tissue under NIR light illumination. Vein images with high quality are critical to biometric identification, which requires segmenting the vein skeleton from the original images accurately. To address this issue, we proposed a vein image segmentation method which based on simple linear iterative clustering (SLIC) method and Niblack threshold method. The SLIC method was used to pre-segment the original images into superpixels and all the information in superpixels were transferred into a matrix (Block Matrix). Subsequently, Niblack thresholding method is adopted to binarize Block Matrix. Finally, we obtained segmented vein images from binarized Block Matrix. According to several experiments, most part of vein skeleton is revealed compared to traditional Niblack segmentation algorithm.
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