Point cloud segmentation is a key step in point cloud processing, and its segmentation quality determines the accuracy of target measurement, pose estimation, and other tasks. This paper proposes a method of depth image (RGB-D) point cloud segmentation using spatial projection. Based on the camera model, RGB-D data characteristics, and the relationship between the image threshold and the target point cloud, a target coordinate system and point cloud regions are established. Further, based on the target coordinate system and the image threshold, the point cloud is transformed to the target coordinate system to highlight the target region and weaken the background region. Also, the projected pixel values are processed by image morphology and the corresponding point cloud region is obtained by segmenting the image. Finally, three test scenarios are established to acquire three different groups of point cloud data, and four methods are adopted to segment and compare point clouds. The spatial projection based method can obtain better point cloud segmentation quality. The relationship among the expansion element, numerical value, and segmentation quality is tested and analyzed. The results show that the spatial projection method is effective and feasible for RGB-D point cloud segmentation.