{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T01:03:00Z","timestamp":1780362180707,"version":"3.54.1"},"reference-count":69,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,24]],"date-time":"2022-12-24T00:00:00Z","timestamp":1671840000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Energy Technology Development and Demonstration Program under the Danish Energy Agency","award":["64015-0046"],"award-info":[{"award-number":["64015-0046"]}]},{"name":"Danish Agency for Institutions and Educational Grants","award":["64015-0046"],"award-info":[{"award-number":["64015-0046"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In general, optical methods for geometrical measurements are influenced by the surface properties of the examined object. In Structure from Motion (SfM), local variations in surface color or topography are necessary for detecting feature points for point-cloud triangulation. Thus, the level of contrast or texture is important for an accurate reconstruction. However, quantitative studies of the influence of surface texture on geometrical reconstruction are largely missing. This study tries to remedy that by investigating the influence of object texture levels on reconstruction accuracy using a set of reference artifacts. The artifacts are designed with well-defined surface geometries, and quantitative metrics are introduced to evaluate the lateral resolution, vertical geometric variation, and spatial\u2013frequency information of the reconstructions. The influence of texture level is compared to variations in capturing range. For the SfM measurements, the ContextCapture software solution and a 50 Mpx DSLR camera are used. The findings are compared to results using calibrated optical microscopes. The results show that the proposed pipeline can be used for investigating the influence of texture on SfM reconstructions. The introduced metrics allow for a quantitative comparison of the reconstructions at varying texture levels and ranges. Both range and texture level are seen to affect the reconstructed geometries although in different ways. While an increase in range at a fixed focal length reduces the spatial resolution, an insufficient texture level causes an increased noise level and may introduce errors in the reconstruction. The artifacts are designed to be easily replicable, and by providing a step-by-step procedure of our testing and comparison methodology, we hope that other researchers will make use of the proposed testing pipeline.<\/jats:p>","DOI":"10.3390\/s23010178","type":"journal-article","created":{"date-parts":[[2022,12,27]],"date-time":"2022-12-27T02:55:07Z","timestamp":1672109707000},"page":"178","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Quantifying the Influence of Surface Texture and Shape on Structure from Motion 3D Reconstructions"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5416-3361","authenticated-orcid":false,"given":"Mikkel Schou","family":"Nielsen","sequence":"first","affiliation":[{"name":"Nano Research, Danish Fundamental Metrology, Kogle All\u00e9 5, DK-2970 H\u00f8rsholm, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4952-8848","authenticated-orcid":false,"given":"Ivan","family":"Nikolov","sequence":"additional","affiliation":[{"name":"Department of Architecture, Design and Media Technology, Faculty of Science, Aalborg University, Rendsburggade 14, DK-9000 Aalborg, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emil Krog","family":"Kruse","sequence":"additional","affiliation":[{"name":"AAU Innovation, Aalborg University, Thomas Manns Vej 25, DK-9220 Aalborg, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J\u00f8rgen","family":"Garn\u00e6s","sequence":"additional","affiliation":[{"name":"Nano Research, Danish Fundamental Metrology, Kogle All\u00e9 5, DK-2970 H\u00f8rsholm, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0762-3713","authenticated-orcid":false,"given":"Claus Br\u00f8ndgaard","family":"Madsen","sequence":"additional","affiliation":[{"name":"Department of Architecture, Design and Media Technology, Faculty of Science, Aalborg University, Rendsburggade 14, DK-9000 Aalborg, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Sch\u00f6ning, J., and Heidemann, G. (2015). Evaluation of multi-view 3D reconstruction software. International Conference on Computer Analysis of Images and Patterns, Springer.","DOI":"10.1007\/978-3-319-23117-4_39"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.enggeo.2009.03.004","article-title":"Close-range terrestrial digital photogrammetry and terrestrial laser scanning for discontinuity characterization on rock cuts","volume":"106","author":"Sturzenegger","year":"2009","journal-title":"Eng. Geol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1016\/j.geomorph.2012.08.021","article-title":"\u2018Structure-from-Motion\u2019photogrammetry: A low-cost, effective tool for geoscience applications","volume":"179","author":"Westoby","year":"2012","journal-title":"Geomorphology"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.cageo.2011.09.012","article-title":"Multiview 3D reconstruction in geosciences","volume":"44","author":"Favalli","year":"2012","journal-title":"Comput. Geosci."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Kersten, T.P., and Lindstaedt, M. (2012). Image-based low-cost systems for automatic 3D recording and modelling of archaeological finds and objects. Euro-Mediterranean Conference, Springer.","DOI":"10.1007\/978-3-642-34234-9_1"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.culher.2012.12.003","article-title":"Multi-image 3D reconstruction data evaluation","volume":"15","author":"Koutsoudis","year":"2014","journal-title":"J. Cult. Herit."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.geomorph.2014.01.006","article-title":"Modeling the topography of shallow braided rivers using Structure-from-Motion photogrammetry","volume":"213","author":"Javernick","year":"2014","journal-title":"Geomorphology"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"573","DOI":"10.5194\/isprsarchives-XL-5-573-2014","article-title":"A comparison of multi-view 3D reconstruction of a rock wall using several cameras and a Laser scanner","volume":"40","author":"Thoeni","year":"2014","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_9","unstructured":"Online, E. (2015). Structure from Motion (SfM) Photogrammetry. Geomorphological Techniques, British Society for Geomorphology Geomorphological Techniques. Chapter 2.2."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Palomaki, R.T., and Sproles, E.A. (2022). Quantifying the Effect of River Ice Surface Roughness on Sentinel-1 SAR Backscatter. Remote Sens., 14.","DOI":"10.3390\/rs14225644"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Ullmann, T., and Stauch, G. (2020). Surface roughness estimation in the orog nuur basin (Southern mongolia) using sentinel-1 SAR time series and ground-based photogrammetry. Remote Sens., 12.","DOI":"10.3390\/rs12193200"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3213","DOI":"10.1007\/s00603-022-02789-9","article-title":"Close-Range Photogrammetry for 3D Rock Joint Roughness Evaluation","volume":"55","author":"Muralha","year":"2022","journal-title":"Rock Mech. Rock Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.autcon.2014.01.004","article-title":"Mobile 3D mapping for surveying earthwork projects using an Unmanned Aerial Vehicle (UAV) system","volume":"41","author":"Siebert","year":"2014","journal-title":"Autom. Constr."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.autcon.2015.02.007","article-title":"Appearance-based material classification for monitoring of operation-level construction progress using 4D BIM and site photologs","volume":"53","author":"Han","year":"2015","journal-title":"Autom. Constr."},{"key":"ref_15","first-page":"3","article-title":"Acquisition and Consecutive Registration of Photogrammetric Point Clouds for Construction Progress Monitoring Using a 4D BIM","volume":"85","author":"Tuttas","year":"2017","journal-title":"J. Photogramm. Remote Sens. Geoinf. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1007\/s00138-011-0394-0","article-title":"An innovative methodology for detection and quantification of cracks through incorporation of depth perception","volume":"24","author":"Jahanshahi","year":"2013","journal-title":"Mach. Vis. Appl."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"4015045","DOI":"10.1061\/(ASCE)CP.1943-5487.0000516","article-title":"Distortion-Free Image Mosaicing for Tunnel Inspection Based on Robust Cylindrical Surface Estimation through Structure from Motion","volume":"30","author":"Chaiyasarn","year":"2016","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1007\/s00138-014-0648-8","article-title":"Visual change detection on tunnel linings","volume":"27","author":"Stent","year":"2016","journal-title":"Mach. Vis. Appl."},{"key":"ref_19","unstructured":"Masson, J.E.N., and Petry, M.R. (2017, January 26\u201328). Comparison of mesh generation algorithms for railroad reconstruction. Proceedings of the Autonomous Robot Systems and Competitions (ICARSC), 2017 IEEE International Conference, Coimbra, Portugal."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"04016047","DOI":"10.1061\/(ASCE)CP.1943-5487.0000616","article-title":"Hierarchical Dense Structure-from-Motion Reconstructions for Infrastructure Condition Assessment","volume":"31","author":"Khaloo","year":"2017","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"045016","DOI":"10.1088\/2051-672X\/ab4cc6","article-title":"3D optical surface profiler for quantifying leaf surface roughness","volume":"7","author":"Abbott","year":"2019","journal-title":"Surf. Topogr. Metrol. Prop."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"106883","DOI":"10.1016\/j.geomorph.2019.106883","article-title":"Terrestrial structure-from-motion: Spatial error analysis of roughness and morphology","volume":"350","author":"Schwendel","year":"2020","journal-title":"Geomorphology"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Nielsen, M.S., Nikolov, I., Kruse, E.K., Garn\u00e6s, J., and Madsen, C.B. (2020). High-Resolution Structure-from-Motion for Quantitative Measurement of Leading-Edge Roughness. Energies, 13.","DOI":"10.3390\/en13153916"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"605","DOI":"10.1002\/esp.4758","article-title":"Evaluation of Terrestrial Laser Scanner and Structure from Motion photogrammetry techniques for quantifying soil surface roughness parameters over agricultural soils","volume":"45","author":"Pfeifer","year":"2020","journal-title":"Earth Surf. Process. Landforms"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Wu, C. (July, January 9). Towards linear-time incremental structure from motion. Proceedings of the 3DTV-Conference, 2013 International Conference, Seattle, WA, USA.","DOI":"10.1109\/3DV.2013.25"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1177\/0309133315615805","article-title":"Structure from motion photogrammetry in physical geography","volume":"40","author":"Smith","year":"2016","journal-title":"Prog. Phys. Geogr. Earth Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.patrec.2014.03.023","article-title":"3D reconstruction methods for digital preservation of cultural heritage: A survey","volume":"50","author":"Gomes","year":"2014","journal-title":"Pattern Recognit. Lett."},{"key":"ref_28","unstructured":"Sch\u00f6ps, T., Sch\u00f6nberger, J.L., Galliani, S., Sattler, T., Schindler, K., Pollefeys, M., and Geiger, A. (July, January 21). A multi-view stereo benchmark with high-resolution images and multi-camera videos. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA."},{"key":"ref_29","first-page":"57","article-title":"Taxonomy of 3D Sensors-A Survey of State-of-the-Art Consumer 3D-Reconstruction Sensors and their Field of Applications","volume":"24","author":"Heidemann","year":"2016","journal-title":"Mach. Graph. Vision"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2420","DOI":"10.1109\/TMECH.2017.2663436","article-title":"Kinect v2 sensor-based mobile terrestrial laser scanner for agricultural outdoor applications","volume":"22","author":"Gregorio","year":"2017","journal-title":"IEEE ASME Trans. Mechatronics"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Bianco, S., Ciocca, G., and Marelli, D. (2018). Evaluating the Performance of Structure from Motion Pipelines. J. Imaging, 4.","DOI":"10.3390\/jimaging4080098"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Nikolov, I., and Madsen, C. (2016). Benchmarking Close-range Structure from Motion 3D Reconstruction Software Under Varying Capturing Conditions. Euro-Mediterranean Conference, Springer.","DOI":"10.1007\/978-3-319-48496-9_2"},{"key":"ref_33","first-page":"115251P.","article-title":"How image capturing setups influence the quality of SfM reconstructions for wind turbine blade inspection","volume":"Volume 11525","author":"Kimata","year":"2020","journal-title":"SPIE Future Sensing Technologies"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"D\u2019Amico, N., and Yu, T. (2017). Accuracy analysis of point cloud modeling for evaluating concrete specimens. SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, International Society for Optics and Photonics.","DOI":"10.1117\/12.2258404"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1002\/esp.3648","article-title":"Investigating the geomorphological potential of freely available and accessible structure-from-motion photogrammetry using a smartphone","volume":"40","author":"Micheletti","year":"2015","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1656","DOI":"10.1002\/esp.3747","article-title":"From experimental plots to experimental landscapes: Topography, erosion and deposition in sub-humid badlands from Structure-from-Motion photogrammetry","volume":"40","author":"Smith","year":"2015","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Kersten, T.P., Omelanowsky, D., and Lindstaedt, M. (2016). Investigations of Low-Cost Systems for 3D Reconstruction of Small Objects. Euro-Mediterranean Conference, Springer.","DOI":"10.1007\/978-3-319-48496-9_41"},{"key":"ref_38","unstructured":"Zhang, L. (2003, January 13\u201316). Shape and motion under varying illumination: Unifying structure from motion, photometric stereo, and multiview stereo. Proceedings of the Ninth IEEE International Conference on Computer Vision, Washington, DC, USA."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1573","DOI":"10.3390\/rs4061573","article-title":"Assessing the Accuracy of Georeferenced Point Clouds Produced via Multi-View Stereopsis from Unmanned Aerial Vehicle (UAV) Imagery","volume":"4","author":"Harwin","year":"2012","journal-title":"Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1117\/12.7972479","article-title":"Photometric method for determining surface orientation from multiple images","volume":"19","author":"Woodham","year":"1980","journal-title":"Opt. Eng."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Wu, L., Ganesh, A., Shi, B., Matsushita, Y., Wang, Y., and Ma, Y. (2010). Robust photometric stereo via low-rank matrix completion and recovery. Asian Conference on Computer Vision, Springer.","DOI":"10.1007\/978-3-642-19318-7_55"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"3014","DOI":"10.1007\/s11263-022-01684-8","article-title":"NormAttention-PSN: A High-frequency Region Enhanced Photometric Stereo Network with Normalized Attention","volume":"130","author":"Ju","year":"2022","journal-title":"Int. J. Comput. Vis."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"519","DOI":"10.5194\/isprs-archives-XLIII-B2-2021-519-2021","article-title":"Investigating 3d Reconstruction Of Non-Collaborative Surfaces through Photogrammetry and Photometric Stereo","volume":"43","author":"Karami","year":"2021","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Toschi, I., Nocerino, E., Hess, M., Menna, F., Sargeant, B., MacDonald, L., Remondino, F., and Robson, S. (2015). Improving Automated 3D Reconstruction Methods via Vision Metrology, International Society for Optics and Photonics.","DOI":"10.1117\/12.2184974"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"856","DOI":"10.1029\/2011JF002289","article-title":"Straightforward reconstruction of 3D surfaces and topography with a camera: Accuracy and geoscience application","volume":"117","author":"James","year":"2012","journal-title":"J. Geophys. Res. Earth Surf."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.rse.2018.03.013","article-title":"Modeling the precision of structure-from-motion multi-view stereo digital elevation models from repeated close-range aerial surveys","volume":"210","author":"Goetz","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Slavcheva, M., Kehl, W., Navab, N., and Ilic, S. (2016). SDF-2-SDF: Highly Accurate 3D Object Reconstruction. European Conference on Computer Vision, Springer.","DOI":"10.1007\/978-3-319-46448-0_41"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1769","DOI":"10.1002\/esp.4125","article-title":"3-D uncertainty-based topographic change detection with structure-from-motion photogrammetry: Precision maps for ground control and directly georeferenced surveys","volume":"42","author":"James","year":"2017","journal-title":"Earth Surf. Process. Landforms"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1007\/s12518-022-00454-y","article-title":"Joint roughness profiling using photogrammetry","volume":"14","author":"Saricam","year":"2022","journal-title":"Appl. Geomat."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1016\/j.jsg.2016.03.009","article-title":"High precision analysis of an embryonic extensional fault-related fold using 3D orthorectified virtual outcrops: The viewpoint importance in structural geology","volume":"86","author":"Tavani","year":"2016","journal-title":"J. Struct. Geol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1016\/j.tecto.2017.08.023","article-title":"Evaluating roughness scaling properties of natural active fault surfaces by means of multi-view photogrammetry","volume":"717","author":"Corradetti","year":"2017","journal-title":"Tectonophysics"},{"key":"ref_52","first-page":"941102","article-title":"Practical usefulness of structure from motion (SfM) point clouds obtained from different consumer cameras","volume":"Volume 9411","author":"Ingwer","year":"2015","journal-title":"Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications"},{"key":"ref_53","unstructured":"Coated abrasives\u2014Grain Size Analysis Parts 1\u20133. Standard No. ISO 6344(1998). Available online: https:\/\/www.iso.org\/standard\/12643.html."},{"key":"ref_54","unstructured":"(2022, October 10). FEPA\u2014Federation of European Producers of Abrasives. Available online: https:\/\/www.fepa-abrasives.com\/abrasive-products\/grains."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Nikolov, I.A., and Madsen, C.B. (2021, January 8\u201310). Quantifying Wind Turbine Blade Surface Roughness using Sandpaper Grit Sizes: An Initial Exploration. Proceedings of the 16th International Conference on Computer Vision Theory and Application, Online Streaming.","DOI":"10.5220\/0010283908010808"},{"key":"ref_56","unstructured":"(2022, October 12). Bentley: ContextCapture. Available online: https:\/\/www.bentley.com\/en\/products\/brands\/contextcapture."},{"key":"ref_57","unstructured":"Girardeau-Montaut, D. (2022, October 12). CloudCompare. Available online: http:\/\/www.cloudcompare.org\/."},{"key":"ref_58","unstructured":"(2022, October 12). Hirox RH-2000 Microscope. Available online: http:\/\/www.hirox-europe.com\/products\/microscope\/RH-2000-digital-microscope.php\/."},{"key":"ref_59","unstructured":"(2022, October 12). PLU NEOX Confocal Microscope. Available online: http:\/\/www.sensofar.com\/."},{"key":"ref_60","unstructured":"(2022, October 12). Sensofar: SensoSCAN. Available online: https:\/\/www.sensofar.com\/metrology\/industry-research\/sneox\/software\/."},{"key":"ref_61","unstructured":"(2022, October 12). Scanning Probe Image Processor (SPIP). Available online: http:\/\/www.nanoscience.com\/products\/afm\/scanning-probe-image-processor\/."},{"key":"ref_62","unstructured":"(2022, October 05). ISO 5436. Available online: https:\/\/www.iso.org\/obp\/ui\/#iso:std:61261:en."},{"key":"ref_63","unstructured":"(2022, October 05). Biovoxxel. Available online: http:\/\/www.biovoxxel.de\/."},{"key":"ref_64","unstructured":"Geometrical Product Specifications (GPS)\u2014Surface Texture: Areal\u2014Part 3: Specification Operators. Standard No. ISO 25178-3(2012). Available online: https:\/\/www.iso.org\/standard\/42895.html."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"R1","DOI":"10.1088\/0953-8984\/17\/1\/R01","article-title":"On the nature of surface roughness with application to contact mechanics, sealing, rubber friction and adhesion","volume":"17","author":"Persson","year":"2005","journal-title":"J. Phys. Condens. Matter"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"013001","DOI":"10.1088\/2051-672X\/aa51f8","article-title":"Quantitative characterization of surface topography using spectral analysis","volume":"5","author":"Jacobs","year":"2017","journal-title":"Surf. Topogr. Metrol. Prop."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/S0141-6359(02)00184-8","article-title":"Calibration of step heights and roughness measurements with atomic force microscopes","volume":"27","author":"Garnaes","year":"2003","journal-title":"Precis. Eng."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1117\/12.521309","article-title":"Comparison of roughness measurement with atomic force microscopy and interference microscopy","volume":"Volume 5188","author":"Duparre","year":"2003","journal-title":"Advanced Characterization Techniques for Optics, Semiconductors, and Nanotechnologies"},{"key":"ref_69","unstructured":"Nikolov, I., Nielsen, M., Krog Kruse, E., Garn\u00e6s, J., Madsen, C., and Hannibal Madsen, M. (2022, December 03). Sandpaper Wind Turbine Blade Benchmark Dataset. Available online: https:\/\/data.mendeley.com\/datasets\/hcgcnm269w\/2."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/1\/178\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:50:03Z","timestamp":1760147403000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/1\/178"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,24]]},"references-count":69,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,1]]}},"alternative-id":["s23010178"],"URL":"https:\/\/doi.org\/10.3390\/s23010178","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,24]]}}}