Difficult peripheral venous access can complicate routine venipuncture, especially when superficial veins are poorly visible under normal lighting conditions. This study aims to develop and preliminarily evaluate a low-cost near-infrared imaging prototype for non-invasive visualization of superficial veins. The prototype consists of a camera without an infrared light filter, an infrared LED illumination module, and an image-processing pipeline implemented in MATLAB. Acquired images were processed using median filtering, histogram-based contrast enhancement, binarization, inversion, and masking procedures to improve vein visibility and outline vascular structures. The prototype was tested on three participants, with three anatomical regions examined for each participant, resulting in nine analyzed images. Vein-to-background contrast and contrast-to-noise ratio were calculated before and after image processing. Across the analyzed images, mean contrast increased from 0.14968 to 0.29088, with a mean relative improvement of 113.40%, while mean CNR increased from 0.48179 to 1.00729, with a mean relative improvement of 130.65%. These results indicate that the proposed system improved the objective visibility of superficial veins under controlled acquisition conditions. The study provides an initial technical basis for further development, while further studies are required to evaluate its performance in larger and more diverse participant groups.
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Ivanov et al. (2026) studied this question.
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