The invention brings forward a traffic
label identification method of vehicle-mounted
laser scanning
point cloud data. The method comprises the following steps: 1,
point cloud real-time preprocessing; 2,
point cloud structure feature obtaining; 3, multi-scale Markov random
field point cloud clustering; and 4, traffic
label identification. The method has the following advantages: "surface-shaped", "linear-shaped" and "scattered" features of point clouds are reinforced, differences between points are enhanced, and while under-segmentation is avoided, reasonable segmentation of the scale of a traffic
label component can be rapidly realized; classification and identification of a traffic label can be conveniently realized from point
cloud data of deficiency of a part of the traffic label, caused by ground object shielding or ground object self-
occlusion; the method can effectively satisfy the requirements for rapid extracting, monitoring and identifying city components at present, can be conveniently promoted to the industry of manned or unmanned navigation and barrier avoiding based on
computer vision, helps a driver to perform navigation and decision-making under complex road conditions, and effectively reduces the
traffic accident probability.