{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T12:05:38Z","timestamp":1769083538649,"version":"3.49.0"},"reference-count":51,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2020,6,30]],"date-time":"2020-06-30T00:00:00Z","timestamp":1593475200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Industry 4.0 comprises a wide spectrum of developmental processes within the management of manufacturing and chain production. Presently, there is a huge effort to automate manufacturing and have automatic control of the production. This intention leads to the increased need for high-quality methods for digitization and object reconstruction, especially in the area of reverse engineering. Commonly used scanning software based on well-known algorithms can correctly process smooth objects. Nevertheless, they are usually not applicable for complex-shaped models with sharp features. The number of the points on the edges is extremely limited due to the principle of laser scanning and sometimes also low scanning resolution. Therefore, a correct edge reconstruction problem occurs. The same problem appears in many other laser scanning applications, i.e., in the representation of the buildings from airborne laser scans for 3D city models. We focus on a method for preservation and reconstruction of sharp features. We provide a detailed description of all three key steps: point cloud segmentation, edge detection, and correct B-spline edge representation. The feature detection algorithm is based on the conventional region-growing method and we derive the optimal input value of curvature threshold using logarithmic least square regression. Subsequent edge representation stands on the iterative algorithm of B-spline approximation where we compute the weighted asymmetric error using the golden ratio. The series of examples indicates that our method gives better or comparable results to other methods.<\/jats:p>","DOI":"10.3390\/ijgi9070422","type":"journal-article","created":{"date-parts":[[2020,6,30]],"date-time":"2020-06-30T09:04:59Z","timestamp":1593507899000},"page":"422","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Sharp Feature Detection as a Useful Tool in Smart Manufacturing"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7963-1942","authenticated-orcid":false,"given":"Jana","family":"Prochazkova","sequence":"first","affiliation":[{"name":"Faculty of Mechanical Engineering, Brno University of Technology, 616 69 Brno, Czech Republic"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2593-7495","authenticated-orcid":false,"given":"David","family":"Proch\u00e1zka","sequence":"additional","affiliation":[{"name":"Faculty of Business and Economics, Mendel University in Brno, 613 00 Brno, Czech Republic"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1390-5285","authenticated-orcid":false,"given":"Jarom\u00edr","family":"Landa","sequence":"additional","affiliation":[{"name":"Faculty of Business and Economics, Mendel University in Brno, 613 00 Brno, Czech Republic"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.compchemeng.2012.06.037","article-title":"Smart manufacturing, manufacturing intelligence and demand-dynamic performance","volume":"47","author":"Davis","year":"2012","journal-title":"Comput. Chem. Eng."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/j.promfg.2018.02.034","article-title":"Industry 4.0\u2014A Glimpse","volume":"20","author":"Vaidya","year":"2018","journal-title":"Procedia Manuf."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Chua, C.K., Leong, K.F., and Lim, C.S. (2010). Rapid Prototyping: Principles and Applications. Rapid Prototyping: Principles and Applicationse, World Scientific Publishing.","DOI":"10.1142\/6665"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1007\/s00170-010-2829-6","article-title":"Direct slicing of cloud data with guaranteed topology for rapid prototyping","volume":"53","author":"Qiu","year":"2011","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/cgf.13147","article-title":"From 3D models to 3D prints: An overview of the processing pipeline","volume":"36","author":"Livesu","year":"2017","journal-title":"Comput. Graph. Forum"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/S0166-3615(01)00140-3","article-title":"Modelling and optimisation of rapid prototyping","volume":"47","author":"Choi","year":"2002","journal-title":"Comput. Ind."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1016\/j.camwa.2007.06.030","article-title":"Golden ratio in science, as random sequence source, its computation and beyond","volume":"56","author":"Sen","year":"2008","journal-title":"J. Comput. Math. Appl."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1016\/j.rcim.2010.08.008","article-title":"Contour curve reconstruction from cloud data for rapid prototyping","volume":"27","author":"Javidrad","year":"2011","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"339","DOI":"10.5194\/isprs-archives-XLII-2-W3-339-2017","article-title":"A review of point clouds segmentation and classification algorithms","volume":"XLII-2\/W3","author":"Grilli","year":"2017","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Nguyen, A., and Le, B. (2013, January 12\u201315). 3D point cloud segmentation: A survey. Proceedings of the 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM), Manila, Philippine.","DOI":"10.1109\/RAM.2013.6758588"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1109\/34.3881","article-title":"Segmentation through Variable-Order Surface Fitting","volume":"10","author":"Besl","year":"1988","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. Arch."},{"key":"ref_12","first-page":"15","article-title":"Improvement of Single Seeded Region Growing Algorithm on Image Segmentation","volume":"18","author":"Nahar","year":"2018","journal-title":"Glob. J. Comput. Sci. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1109\/34.295913","article-title":"Seeded Region Growing","volume":"6","author":"Adams","year":"1994","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. Arch."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.cageo.2016.11.002","article-title":"A region-growing approach for automatic outcrop fracture extraction from a three-dimensional point cloud","volume":"99","author":"Wang","year":"2017","journal-title":"Comput. Geosci."},{"key":"ref_15","first-page":"79","article-title":"Robust surface segmentation and edge feature lines extraction from fractured fragments of relics","volume":"2","author":"Xu","year":"2015","journal-title":"J. Comput. Des. Eng."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.isprsjprs.2015.01.011","article-title":"Octree-based region growing for point cloud segmentation","volume":"104","author":"Vo","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Ni, H., Lin, X., Ning, X., and Zhang, J. (2016). Edge Detection and Feature Line Tracing in 3D-Point Clouds by Analyzing Geometric Properties. Remote Sens., 8.","DOI":"10.3390\/rs8090710"},{"key":"ref_18","first-page":"267","article-title":"Detection of closed sharp edges in point clouds using normal estimation and graph theory","volume":"39","author":"Demaris","year":"2007","journal-title":"Comput. Aided Des."},{"key":"ref_19","unstructured":"Jiang, X.Y., Bunke, H., and Meier, U. (1996, January 2\u20134). Fast range image segmentation using high-level segmentation primitives. Proceedings of the Third IEEE Workshop on Applications of Computer Vision, Sarasota, FL, USA."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1111\/j.1467-8659.2007.01016.x","article-title":"Efficent Ransac for point cloud shape detection","volume":"26","author":"Schnabel","year":"2007","journal-title":"Comput. Graph. Forum"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1111\/cgf.12802","article-title":"A Survey of Surface Reconstruction from Point Clouds","volume":"36","author":"Berger","year":"2016","journal-title":"Comput. Graph Forum"},{"key":"ref_22","unstructured":"Benes, B., and Chen, M. (2013). Surface reconstruction through point set structuring. Computer Graphics Forum, Wiley."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"15272","DOI":"10.1109\/ACCESS.2019.2891959","article-title":"3D Incomplete Point Cloud Surfaces Reconstruction With Segmentation and Feature-Enhancement","volume":"7","author":"Wang","year":"2019","journal-title":"IEEE Access"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1145\/2661229.2661241","article-title":"Morfit: Interactive surface reconstruction from incomplete point clouds with curve-driven topology and geometry control","volume":"33","author":"Yin","year":"2014","journal-title":"ACM Trans. Graph."},{"key":"ref_25","unstructured":"Desbrun, M., and Pottmann, H. (2005). Smooth features lines on surface meshes. Eurographics Symposium on Geometry Processing, Eurographics Association."},{"key":"ref_26","first-page":"127","article-title":"Automatic detection of geodesic ridges and ravines on polygonal surface","volume":"15","author":"Ohtake","year":"2001","journal-title":"J. Three Dimens. Images"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Farin, G., Hamann, B., and Hagen, H. (2003). Crest lines extraction from 3D triangulated meshes. Hierarchical and Geometrical Methods in Scientific Visualization, Springer.","DOI":"10.1007\/978-3-642-55787-3"},{"key":"ref_28","first-page":"142","article-title":"Classifying the Dimensional Variation in Additive Manufactured Parts From Laser-Scanned Three-Dimensional Point Cloud Data Using Machine Learning Approaches","volume":"139","author":"Tootooni","year":"2017","journal-title":"J. Manuf. Sci. Eng."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1382","DOI":"10.1016\/j.cad.2013.06.004","article-title":"A comprehensive process of reverse engineering from 3D meshes to CAD models","volume":"45","author":"Beniere","year":"2013","journal-title":"Comput. Aided Des."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1347","DOI":"10.1007\/s00170-015-7071-9","article-title":"An improved slicing algorithm with efficient contour construction using STL files","volume":"80","author":"Zhang","year":"2015","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1309","DOI":"10.1016\/j.cad.2004.02.001","article-title":"NURBS-based adaptive slicing for efficient rapid prototyping","volume":"36","author":"Ma","year":"2004","journal-title":"Comput. Aided Des."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1080\/16864360.2016.1223443","article-title":"Generating point clouds for slicing free-form objects for 3-D printing","volume":"14","author":"Oropallo","year":"2017","journal-title":"Comput. Aided Des. Appl."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1186\/s42492-019-0013-x","article-title":"Slicing and support structure generation for 3D printing directly on B-rep models","volume":"2","author":"Shi","year":"2019","journal-title":"Vis. Comput. Ind. Biomed. Art"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"3149","DOI":"10.1007\/s00170-018-1772-9","article-title":"Nonplanar slicing and path generation methods for robotic additive manufacturing","volume":"96","author":"Zhao","year":"2018","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"ref_35","first-page":"368","article-title":"Automated cross-sectional shape recovery of 3D branching structures from point cloud","volume":"5","author":"Kresslein","year":"2018","journal-title":"J. Comput. Des. Eng."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Liu, W., Sun, J., Li, W., Hu, T., and Wang, P. (2019). Deep Learning on Point Clouds and Its Application: A Survey. Sensors, 19.","DOI":"10.3390\/s19194188"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Griffiths, D., and Boehm, J. (2019). A Review on Deep Learning Techniques for 3D Sensed Data Classification. Remote Sens., 11.","DOI":"10.3390\/rs11121499"},{"key":"ref_38","unstructured":"Guo, Y., Wang, H., Hu, Q., Liu, H., Liu, L., and Bennamoun, M. (2019). Deep Learning for 3D Point Clouds: A Survey. arXiv."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Lee, D., Quan, I., Wu, C., Wu, J., Tamir, D., and Rishe, N. (2020, January 6\u20138). Optimizing B-Spline Surface Reconstruction for Sharp Feature Preservation. Proceedings of the 10th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA.","DOI":"10.1109\/CCWC47524.2020.9031263"},{"key":"ref_40","first-page":"81","article-title":"Novel algorithms for 3D surface point cloud boundary detection and edge reconstruction","volume":"6","author":"Mineo","year":"2019","journal-title":"J. Comput. Des. Eng."},{"key":"ref_41","first-page":"985","article-title":"Feature sensitive three-dimensional point cloud simplification using support vector regression","volume":"27","author":"Markovic","year":"2019","journal-title":"Tech. Gaz."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Bazazian, D., Casas, J.R., and Ruiz-Hidalgo, J. (2015, January 23\u201325). Fast and Robust Edge Extraction in Unorganized Point Clouds. Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA), Adelaide, Australia.","DOI":"10.1109\/DICTA.2015.7371262"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Wang, Y.X., Wang, J., Chen, X., Chu, T., Liu, M., and Yang, T. (2018). Feature Surface Extraction and Reconstruction from Industrial Components Using Multistep Segmentation and Optimization. Remote Sens., 10.","DOI":"10.3390\/rs10071073"},{"key":"ref_44","first-page":"141","article-title":"Modeling connected regions in arbitrary planar point clouds by robust B-spline approximation","volume":"76","author":"Balzer","year":"2008","journal-title":"Robot. Auton. Syst."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Jolliffe, I.T. (1986). Principal Component Analysis, Springer.","DOI":"10.1007\/978-1-4757-1904-8"},{"key":"ref_46","unstructured":"Banchoff, T., Gaffney, T., and McCrory, C. (1982). Cups of the Gauss Map. Research Notes in Mathematics, Pitman."},{"key":"ref_47","unstructured":"Middel, A., Scheler, I., and Hagen, H. (2010). Methods for feature detection in point cloud. Visualization of Large and Unstructured Data Sets\u2013IRTG Workshop, Schloss Dagstuhl\u2013Leibniz-Zentrum fuer Informatik."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Piegl, L., and Tiller, W. (1997). The NURBS Book, Springer.","DOI":"10.1007\/978-3-642-59223-2"},{"key":"ref_49","unstructured":"de Boor, C. (2001). A Practical Guide to Splines, Springer."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Blake, A., and Isard, M. (1998). The Active Contours, Springer.","DOI":"10.1007\/978-1-4471-1555-7"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1145\/1138450.1138453","article-title":"Fitting B-spline curves to point clouds by curvature-based squared distance minimization","volume":"25","author":"Wang","year":"2006","journal-title":"ACM Trans. Graph."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/7\/422\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:45:21Z","timestamp":1760175921000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/7\/422"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,30]]},"references-count":51,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2020,7]]}},"alternative-id":["ijgi9070422"],"URL":"https:\/\/doi.org\/10.3390\/ijgi9070422","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,30]]}}}