Complex Substation Scene Segmentation Method Based on Optimized Straight Line Detection

This paper proposes a scene segmentation method based on optimized line detection to address the difficulty of segmenting spatially independent equipment in complex substation scenes. The method first employs the RANSAC method to simulate the ground plane and extract the ground point cloud. Then, it projects the 3D point cloud scene onto a 2D plane to obtain a 2D image of the substation. Straight line segments of the power line are extracted from the image using the edge detection algorithm and an improved line detection algorithm. The straight line segments that do not belong to the power line are filtered out using the surrounding features of the 3D point corresponding to the 2D point on the line. The power line's straight line segment is extended using the region-growing algorithm. Finally, the power line clustering is completed using European clustering based on the three-dimensional coordinates of the two ends of the power line, thereby completing the scene segmentation. Experimental results show that the proposed method can effectively segment substation equipment. Compared to traditional segmentation methods, this method has an average power line identification accuracy of 14% higher.