Traffic markings detection for autonomous driving based on machine vision

Accurate detection of traffic markings is critical for the development of advanced driver-assistance systems and autonomous vehicles. This paper proposes a comprehensive method for detecting lane markings in road images using advanced image processing techniques based on machine vision. The method includes transforming RGB images to HSI format to enhance lane marking visibility, applying image smoothing to reduce noise and improve clarity. The morphological processing and specific filters is applied to refine and isolate lane markings from the background. The detected lane markings are overlaid on the original images for visualization, and the results are outputted for further analysis. Extensive testing under diverse road conditions and lighting environments demonstrates the robustness and effectiveness of the proposed method in accurately detecting lane markings for unmanned.