To address the limitations of current laser mole removal equipment, such as reliance on manual observation and operation by physicians, which leads to low positioning accuracy, potential damage to surrounding tissue, and unstable treatment outcomes, this paper proposes an intelligent laser mole removal system based on machine vision. The system adopts a true coaxial optical path design to ensure high consistency between the visual capture and laser irradiation paths. It comprises three core modules: image acquisition, image processing, and laser scanning. A charge-coupled device (CCD) camera is used for real-time image capture. Open-source computer vision library (OpenCV) algorithms perform image enhancement, threshold segmentation, and contour extraction to accurately identify the location and shape of moles. The laser scanning path is precisely controlled via a galvo mirror control card, enabling efficient treatment of the nevi. Experimental results demonstrate that the system can effectively identify and remove pigmented moles on simulated skin models, with a significant reduction in melanin observed post-treatment. This research validates the feasibility of integrating machine vision into laser mole removal and provides a technical reference for the automation and intellectualization of medical aesthetic equipment.