To quickly and accurately obtain the outer dimensions of small vehicles, improve the efficiency of motor vehicle inspection organizations, and reduce cost inputs, a high-precision measurement method for small vehicle outer dimensions based on RGB-D cameras is proposed. A hardware system for on-site measurements was built using a REALSENSE D455 camera and a Raspberry Pi development board. The target vehicles were extracted using the YOLOv8 model for object detection and instance segmentation. In view of the problems existing in RGB-D camera capturing vehicle images and generating point clouds, depth image repair and point cloud filtering are performed respectively, and the outline size parameters are automatically extracted after merging the point clouds. In experiments, outdoor field tests were conducted on four different models of small cars. The results indicate that the method’s measurement errors for vehicle outer dimensions is less than ±1%, meeting the requirements of national standards.