{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T21:05:04Z","timestamp":1776287104749,"version":"3.50.1"},"reference-count":68,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2023,6,16]],"date-time":"2023-06-16T00:00:00Z","timestamp":1686873600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In close-range photogrammetry, circular-coded targets (CCTs) are a reliable method to solve the issue of image correspondence. Currently, the identification methods for CCTs are very mature, but complex illumination conditions are still a key factor restricting identification. This article proposes an adaptive homomorphic filtering (AHF) algorithm to solve this issue, utilizing homomorphic filtering (HF) to eliminate the influence of uneven illumination. However, HF parameters vary with different lighting types. We use a genetic algorithm (GA) to carry out global optimization and take the identification result as the objective function to realize automatic parameter adjustment. This is different from the optimization strategy of traditional adaptive image enhancement methods, so the most significant advantage of the proposed algorithm lies in its automation and universality, i.e., users only need to input photos without considering the type of lighting conditions. As a preprocessing algorithm, we conducted experiments combining advanced commercial photogrammetric software and traditional identification methods, respectively. We cast stripe- and lattice-structured light to create complex lighting conditions, including uneven lighting, dense shadow areas, and elliptical light spots. Experiments showed that our algorithm significantly improves the robustness and accuracy of CCT identification methods under complex lighting conditions. Given the perfect performance under stripe-structured light, this algorithm can provide a new idea for the fusion of close-range photogrammetry and structured light. This algorithm helps to improve the quality and accuracy of photogrammetry and even helps to improve the decision making and planning process of photogrammetry.<\/jats:p>","DOI":"10.3390\/rs15123151","type":"journal-article","created":{"date-parts":[[2023,6,16]],"date-time":"2023-06-16T08:56:01Z","timestamp":1686905761000},"page":"3151","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["AHF: An Automatic and Universal Image Preprocessing Algorithm for Circular-Coded Targets Identification in Close-Range Photogrammetry under Complex Illumination Conditions"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6074-0754","authenticated-orcid":false,"given":"Hang","family":"Shang","sequence":"first","affiliation":[{"name":"College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130061, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5014-7794","authenticated-orcid":false,"given":"Changying","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130061, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Moyano, J., Nieto-Juli\u00e1n, J.E., Bienvenido-Huertas, D., and Mar\u00edn-Garc\u00eda, D. (2020). Validation of Close-Range Photogrammetry for Architectural and Archaeological Heritage: Analysis of Point Density and 3D Mesh Geometry. Remote Sens., 12.","DOI":"10.3390\/rs12213571"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1007\/s12520-022-01502-9","article-title":"A Detailed Method for Creating Digital 3D Models of Human Crania: An Example of Close-Range Photogrammetry Based on the Use of Structure-from-Motion (SfM) in Virtual Anthropology","volume":"14","author":"Lauria","year":"2022","journal-title":"Archaeol. Anthrop. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Murtiyoso, A., Pellis, E., Grussenmeyer, P., Landes, T., and Masiero, A. (2022). Towards Semantic Photogrammetry: Generating Semantically Rich Point Clouds from Architectural Close-Range Photogrammetry. Sensors, 22.","DOI":"10.3390\/s22030966"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1007\/s40725-019-00094-3","article-title":"Structure from Motion Photogrammetry in Forestry: A Review","volume":"5","author":"Iglhaut","year":"2019","journal-title":"Curr. For. Rep."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"111302","DOI":"10.1016\/j.measurement.2022.111302","article-title":"Measurement Methods of 3D Shape of Large-Scale Complex Surfaces Based on Computer Vision: A Review","volume":"197","author":"Shang","year":"2022","journal-title":"Measurement"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1142\/S0218001401001222","article-title":"Circular Coded Target for Automation of Optical 3D-Measurement and Camera Calibration","volume":"15","author":"Ahn","year":"2001","journal-title":"Int. J. Pattern Recogn."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1080\/10095020.2020.1843376","article-title":"Feature Detection and Description for Image Matching: From Hand-Crafted Design to Deep Learning","volume":"24","author":"Chen","year":"2021","journal-title":"Geo-Spat. Inf. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Sharma, S.K., Jain, K., and Shukla, A.K. (2023). A Comparative Analysis of Feature Detectors and Descriptors for Image Stitching. Appl. Sci., 13.","DOI":"10.3390\/app13106015"},{"key":"ref_9","first-page":"49","article-title":"Detectors and Descriptors for Photogrammetric Applications. International Archives of the Photogrammetry","volume":"36","author":"Remondino","year":"2006","journal-title":"Remote Sens. Spat. Inf. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Forero, M.G., Mambuscay, C.L., Monroy, M.F., Miranda, S.L., M\u00e9ndez, D., Valencia, M.O., and Gomez Selvaraj, M. (2021). Comparative Analysis of Detectors and Feature Descriptors for Multispectral Image Matching in Rice Crops. Plants, 10.","DOI":"10.3390\/plants10091791"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.isprsjprs.2019.11.017","article-title":"An Integrated Photogrammetric and Photoclinometric Approach for Illumination-Invariant Pixel-Resolution 3D Mapping of the Lunar Surface","volume":"159","author":"Liu","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sen."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1111\/phor.12400","article-title":"Exploiting Light Directionality for Image-Based 3d Reconstruction of Non-Collaborative Surfaces","volume":"37","author":"Karami","year":"2022","journal-title":"Photogramm. Rec."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.oceaneng.2016.04.016","article-title":"Low Cost Digital Close Range Photogrammetric Measurement of an As-Built Anchor Handling Tug Hull","volume":"119","author":"Tang","year":"2016","journal-title":"Ocean Eng."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Liu, Y., Su, X., Guo, X., Suo, T., and Yu, Q. (2021). A Novel Concentric Circular Coded Target, and Its Positioning and Identifying Method for Vision Measurement under Challenging Conditions. Sensors, 21.","DOI":"10.3390\/s21030855"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"901","DOI":"10.1111\/0031-868X.00099","article-title":"Innovations in Automation for Vision Metrology Systems","volume":"15","author":"Fraser","year":"1997","journal-title":"Photogramm. Rec."},{"key":"ref_16","first-page":"441","article-title":"Automated Procedures with Coded Targets in Industrial Vision Metrology","volume":"68","author":"Hattori","year":"2002","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Tushev, S., Sukhovilov, B., and Sartasov, E. (2018, January 15\u201318). Robust Coded Target Recognition in Adverse Light Conditions. Proceedings of the 2018 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM), Moscow, Russia.","DOI":"10.1109\/ICIEAM.2018.8728806"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2280","DOI":"10.1016\/j.patcog.2014.01.005","article-title":"Automatic Generation and Detection of Highly Reliable Fiducial Markers under Occlusion","volume":"47","year":"2014","journal-title":"Pattern Recogn."},{"key":"ref_19","first-page":"56","article-title":"Optical 3-D Measurement Systems for Quality Control in Industry","volume":"29","author":"Schneider","year":"1993","journal-title":"Int. Arch. Photogramm. Remote Sens."},{"key":"ref_20","first-page":"80","article-title":"The Development of New Coded Targets for Automated Point Identification and Non-Contact 3D Surface Measurements","volume":"5","author":"Knyaz","year":"1998","journal-title":"Int. Arch. Photogramm. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2293","DOI":"10.3788\/OPE.20122010.2293","article-title":"Correcting Error on Recognition of Coded Points for Photogrammetry","volume":"20","author":"Yang","year":"2012","journal-title":"Opt. Precis. Eng."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"208","DOI":"10.20965\/jrm.2015.p0208","article-title":"Recognition of Center Circles for Encoded Targets in Digital Close-Range Industrial Photogrammetry","volume":"27","author":"Xuemei","year":"2015","journal-title":"J. Robot. Mechatron."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"125","DOI":"10.5194\/isprs-archives-XLIV-2-W1-2021-125-2021","article-title":"Deep Learning for Coded Target Detection","volume":"44","author":"Kniaz","year":"2021","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1007\/s12200-012-0278-6","article-title":"An Ellipse Detection Method for 3D Head Image Fusion Based on Color-Coded Mark Points","volume":"5","author":"Guo","year":"2012","journal-title":"Front. Optoelectron."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3727","DOI":"10.1016\/j.ijleo.2014.03.009","article-title":"Design of a Color Coded Target for Vision Measurements","volume":"125","author":"Yang","year":"2014","journal-title":"Optik"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1111\/phor.12070","article-title":"A Practical Target Recognition System for Close Range Photogrammetry","volume":"29","author":"Shortis","year":"2014","journal-title":"Photogramm. Rec."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Tushev, S., Sukhovilov, B., and Sartasov, E. (2017, January 16\u201319). Architecture of Industrial Close-Range Photogrammetric System with Multi-Functional Coded Targets. Proceedings of the 2017 2nd International Ural Conference on Measurements (UralCon), Chelyabinsk, Russia.","DOI":"10.1109\/URALCON.2017.8120748"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Wang, Q., Liu, Y., Guo, Y., Wang, S., Zhang, Z., Cui, X., and Zhang, H. (2022). A Robust and Effective Identification Method for Point-Distributed Coded Targets in Digital Close-Range Photogrammetry. Remote Sens., 14.","DOI":"10.3390\/rs14215377"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Tinkham, W.T., and Swayze, N.C. (2021). Influence of Agisoft Metashape Parameters on UAS Structure from Motion Individual Tree Detection from Canopy Height Models. Forests, 12.","DOI":"10.3390\/f12020250"},{"key":"ref_30","unstructured":"Forbes, K., Voigt, A., and Bodika, N. (June, January 27). An Inexpensive, Automatic and Accurate Camera Calibration Method. Proceedings of the Thirteenth Annual South African Workshop on Pattern Recognition, Salerno, Italy."},{"key":"ref_31","first-page":"288","article-title":"Automated Reference Point Detection in Close Range Photogrammetry","volume":"25","author":"Zhou","year":"2007","journal-title":"J. Appl. Sci."},{"key":"ref_32","first-page":"407","article-title":"A Robust Recognition Algorithm for Encoded Targets in Close-Range Photogrammetry","volume":"28","author":"Xia","year":"2012","journal-title":"J. Inf. Sci. Eng."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Li, W., Liu, G., Zhu, L., Li, X., Zhang, Y., and Shan, S. (2016, January 3\u20137). Efficient Detection and Recognition Algorithm of Reference Points in Photogrammetry. Proceedings of the Optics, Photonics and Digital Technologies for Imaging Applications IV, SPIE, Brussels, Belgium.","DOI":"10.1117\/12.2225416"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"42454","DOI":"10.1364\/OE.470990","article-title":"High-Accuracy Camera Calibration Method Based on Coded Concentric Ring Center Extraction","volume":"30","author":"Yu","year":"2022","journal-title":"Opt. Express"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3779","DOI":"10.1007\/s11440-021-01343-1","article-title":"A Table Method for Coded Target Decoding with Application to 3-D Reconstruction of Soil Specimens during Triaxial Testing","volume":"16","author":"Xia","year":"2021","journal-title":"Acta Geotech."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"16926","DOI":"10.1364\/OE.20.016926","article-title":"Hyper-Accurate Flexible Calibration Technique for Fringe-Projection-Based Three-Dimensional Imaging","volume":"20","author":"Vo","year":"2012","journal-title":"Opt. Express"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"12026","DOI":"10.1364\/OE.24.012026","article-title":"Generic Precise Augmented Reality Guiding System and Its Calibration Method Based on 3D Virtual Model","volume":"24","author":"Liu","year":"2016","journal-title":"Opt. Express"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Shortis, M.R., Seager, J.W., Robson, S., and Harvey, E.S. (2003, January 10). Automatic Recognition of Coded Targets Based on a Hough Transform and Segment Matching. Proceedings of the Videometrics VII, SPIE, Santa Clara, CA, USA.","DOI":"10.1117\/12.476172"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Li, Y., Li, H., Gan, X., Qu, J., and Ma, X. (2020, January 26\u201328). Location of Circular Retro-Reflective Target Based on Micro-Vision. Proceedings of the 2019 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems, SPIE, San Diego, CA, USA.","DOI":"10.1117\/12.2543291"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"278","DOI":"10.1109\/JSTARS.2022.3224543","article-title":"An Automatic and Accurate Method for Marking Ground Control Points in Unmanned Aerial Vehicle Photogrammetry","volume":"16","author":"Kong","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1007\/s10044-012-0281-y","article-title":"A New Radial Symmetry Measure Applied to Photogrammetry","volume":"16","author":"Dosil","year":"2013","journal-title":"Pattern Anal. Appl."},{"key":"ref_42","unstructured":"D\u00f6ring, T., Meysel, F., and Reulke, R. (2006, January 25\u201327). Autonomous Calibration of Moving Line Scanners with Coded Photogrammetric Targets Recognition. Proceedings of the ISPRS Commission V Symposium on Image Engineering and Vision Metrology, Dresden, Germany."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"037005","DOI":"10.1117\/1.3364057","article-title":"Exploitation of Photogrammetry Measurement System","volume":"49","author":"Zhang","year":"2010","journal-title":"Opt. Eng."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"800","DOI":"10.1016\/j.optlaseng.2011.12.011","article-title":"A Four-Camera Videogrammetric System for 3-D Motion Measurement of Deformable Object","volume":"50","author":"Hu","year":"2012","journal-title":"Opt. Laser Eng."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Chen, R., Zhong, K., Li, Z., Liu, M., and Zhan, G. (2016, January 12\u201314). An Accurate and Reliable Circular Coded Target Detection Algorithm for Vision Measurement. Proceedings of the Optical Metrology and Inspection for Industrial Applications IV, SPIE, Beijing, China.","DOI":"10.1117\/12.2245590"},{"key":"ref_46","first-page":"221","article-title":"A Stable Decoding Algorithm based on Circular Coded Target","volume":"12","author":"Zeng","year":"2018","journal-title":"ICIC Express Lett."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","article-title":"A Threshold Selection Method from Gray-Level Histograms","volume":"9","author":"Otsu","year":"1979","journal-title":"IEEE Syst. Man Cybern. B"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Canny, J. (1986). A Computational Approach to Edge Detection. IEEE Trans. Pattern Anal., 679\u2013698.","DOI":"10.1109\/TPAMI.1986.4767851"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"558","DOI":"10.1016\/j.isprsjprs.2010.06.003","article-title":"Close Range Photogrammetry for Industrial Applications","volume":"65","author":"Luhmann","year":"2010","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Zheng, F., Wackrow, R., Meng, F.-R., Lobb, D., and Li, S. (2020). Assessing the Accuracy and Feasibility of Using Close-Range Photogrammetry to Measure Channelized Erosion with a Consumer-Grade Camera. Remote Sens., 12.","DOI":"10.3390\/rs12111706"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1016\/j.ijleo.2019.02.118","article-title":"Uneven Illumination Correction of Digital Images: A Survey of the State-of-the-Art","volume":"183","author":"Dey","year":"2019","journal-title":"Optik"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"108700","DOI":"10.1016\/j.measurement.2020.108700","article-title":"Robust Circular Marker Localization under Non-Uniform Illuminations Based on Homomorphic Filtering","volume":"170","author":"Dong","year":"2021","journal-title":"Measurement"},{"key":"ref_53","first-page":"590","article-title":"A Novel Thresholding Methodology Using WSI EMD and Adaptive Homomorphic Filter","volume":"67","author":"Venkatappareddy","year":"2019","journal-title":"IEEE Trans. Circuits-II"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Fan, Y., Zhang, L., Guo, H., Hao, H., and Qian, K. (2020). Image Processing for Laser Imaging Using Adaptive Homomorphic Filtering and Total Variation. Photonics, 7.","DOI":"10.3390\/photonics7020030"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"108566","DOI":"10.1016\/j.compeleceng.2022.108566","article-title":"Homomorphic Filtering for the Image Enhancement Based on Fractional-Order Derivative and Genetic Algorithm","volume":"106","author":"Gamini","year":"2023","journal-title":"Comput. Electr. Eng."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.neucom.2023.02.006","article-title":"Deep Learning Based Object Detection for Resource Constrained Devices-Systematic Review, Future Trends and Challenges Ahead","volume":"531","author":"Kamath","year":"2023","journal-title":"Neurocomputing"},{"key":"ref_57","first-page":"8680","article-title":"Application of a Genetic Algorithm with a Fuzzy Objective Function for Optimized Siting of Electric Vehicle Charging Devices in Urban Road Networks","volume":"23","year":"2021","journal-title":"IEEE T. Intell. Transp."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Vivek, M.B., Manju, N., and Vijay, M.B. (2016, January 30\u201331). Machine Learning Based Food Recipe Recommendation System. Proceedings of the International Conference on Cognition and Recognition, ICCR, Karnataka, India.","DOI":"10.1007\/978-981-10-5146-3_2"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"25123","DOI":"10.1109\/JSEN.2021.3065757","article-title":"An Optimization Model for Process Traceability in Case-Based Reasoning Based on Ontology and the Genetic Algorithm","volume":"21","author":"Chen","year":"2021","journal-title":"IEEE Sens. J."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1016\/j.cie.2011.11.025","article-title":"A Genetic Algorithm Based Approach to Vehicle Routing Problem with Simultaneous Pick-up and Deliveries","volume":"62","author":"Tasan","year":"2012","journal-title":"Comput. Ind. Eng."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.tcs.2015.01.002","article-title":"Improved Time Complexity Analysis of the Simple Genetic Algorithm","volume":"605","author":"Oliveto","year":"2015","journal-title":"Theor. Comput. Sci."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1007\/s00138-020-01159-1","article-title":"Circular Coded Target System for Industrial Applications","volume":"32","year":"2021","journal-title":"Mach. Vis. Appl."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.isprsjprs.2015.09.005","article-title":"Recent Developments in Large-Scale Tie-Point Matching","volume":"115","author":"Hartmann","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Yang, K., Hu, Z., Liang, Y., Fu, Y., Yuan, D., Guo, J., Li, G., and Li, Y. (2022). Automated Extraction of Ground Fissures Due to Coal Mining Subsidence Based on UAV Photogrammetry. Remote Sens., 14.","DOI":"10.3390\/rs14051071"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1186\/s40494-023-00897-5","article-title":"Combination of Terrestrial Laser Scanning and UAV Photogrammetry for 3D Modelling and Degradation Assessment of Heritage Building Based on a Lighting Analysis: Case Study\u2014St. Adalbert Church in Gdansk, Poland","volume":"11","author":"Tysiac","year":"2023","journal-title":"Herit. Sci."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"108081","DOI":"10.1016\/j.measurement.2020.108081","article-title":"Measurement of Complex Freeform Additively Manufactured Parts by Structured Light and Photogrammetry","volume":"164","author":"Catalucci","year":"2020","journal-title":"Measurement"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Br\u00e4uer-Burchardt, C., Munkelt, C., Bleier, M., Heinze, M., Gebhart, I., K\u00fchmstedt, P., and Notni, G. (2023). Underwater 3D Scanning System for Cultural Heritage Documentation. Remote Sens., 15.","DOI":"10.3390\/rs15071864"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1007\/s00773-020-00761-2","article-title":"Study of 3D Measurement of Ships Using Dense Stereo Vision: Towards Application in Automatic Berthing Systems","volume":"26","author":"Nomura","year":"2021","journal-title":"J. Mar. Sci. Technol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/12\/3151\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:56:29Z","timestamp":1760126189000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/12\/3151"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,16]]},"references-count":68,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2023,6]]}},"alternative-id":["rs15123151"],"URL":"https:\/\/doi.org\/10.3390\/rs15123151","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,16]]}}}