A Point Cloud Contour Extraction Method based on Plane Segmentation
DOI:
https://doi.org/10.54097/jfqs4b09Keywords:
Three-dimensional Image Processing, Object Detection, Random Sample Consensus, Contour Extraction, Point Cloud ProcessingAbstract
A method based on plane segmentation and dimensionality reduction for extracting incomplete and slow contour features of object point clouds is proposed. The method consists of two main steps: plane segmentation and contour extraction. In plane segmentation, the random sample consensus (Random Sample Consensus, RANSAC) algorithm is optimized based on principal component analysis (Principal Component Analysis, PCA); the optimized planar point cloud is then subjected to dimensionality reduction, and the contour features are extracted using gradients. Experimental results show that the method can effectively segment point clouds and extract the contours of target surfaces, and has great potential for application in industrial inspection and other fields.
Downloads
References
Emelyanov, A.; Skala, V. Surface Reconstruction from Problem Point Clouds. International Conference on Planarization Technology 2002, 5, 6-75.
Kim, J.; Jin, M.; Park, S.H.; Chung, S.Y.; Hwang, M.J. Task Space Trajectory Planning for Robot Manipulators to Follow 3-D Curved Contours. Electronics 2020, 9, 1424.
Hackel, T.; Wegner, J.D.; Schindler, K. Joint classification and contour extraction of large 3D point clouds. ISPRS Journal of Photogrammetry and Remote Sensing 2017, 130, 231-245.
Venkatesh, Y.V.; Raja, S.K.; Ramya, N. Multiple contour extraction from graylevel images using an artificial neural network. IEEE Transactions on Image Processing 2006, 15, 892-899.
Borrmann, D; Elseberg, J.; Lingemann, K.; Nüchter, A. The 3D Hough Transform for plane detection in point clouds: A review and a new accumulator design. 3D Research 2011, 2, 1-13.
Chauve, A.L.; Labatut, P.; Pons, J.P. Robust piecewise-planar 3D reconstruction and completion from large-scale unstructured point data. 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Francisco, USA, 13-18 June 2010.
Nan, L. L.; Wonka, P. PolyFit: Polygonal Surface Reconstruction from Point Clouds. 2017 IEEE International Conference on Computer Vision (ICCV), Venice, Italy, 22-29 October 2017.
Mencl, R. A Graph–Based Approach to Surface Reconstruction. Computer Graphics Forum 1995, 14, 445-456.
Chen, X.J.; Yu, K. Feature Line Generation and Regularization from Point Clouds. IEEE Transactions on Geoscience and Remote Sensing 2019, 57, 9779-9790.
Edelsbrunner, H; Mücke, E. Three-dimensional alpha shapes. 3D Research 1994, 2, 1-13.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Frontiers in Computing and Intelligent Systems
This work is licensed under a Creative Commons Attribution 4.0 International License.
