A fast and efficient segmentation algorithm is proposed for scenes in which multiple plate-shaped objects are placed in an overlapping manner. The algorithm makes full use of the characteristics of the ordered point cloud, and combines the top-down and bottom-up segmentation strategies. The Random Sample Consensus (RANSAC) algorithm is used to quickly extract the three-dimensional planar point set according to the spatial position and normal vector of the three-dimensional point from the three-dimensional point cloud. The image coordinates corresponding to the extracted planar point set are mapped into a binary image, and are divided into a plurality of connected planar regions by the connected region analysis. Then, the glue algorithm is used to quickly merge these regions, and the larger weakly connected regions are subjected to the fracture correction, so as to obtain the final segmentation result. The experimental results show that compared with the region growing algorithm, the proposed algorithm can obtain better segmentation results, and the algorithm efficiency is greatly improved.