{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T14:00:21Z","timestamp":1776088821230,"version":"3.50.1"},"reference-count":44,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2017,9,7]],"date-time":"2017-09-07T00:00:00Z","timestamp":1504742400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Crack assessment is an essential process in the maintenance of concrete structures. In general, concrete cracks are inspected by manual visual observation of the surface, which is intrinsically subjective as it depends on the experience of inspectors. Further, it is time-consuming, expensive, and often unsafe when inaccessible structural members are to be assessed. Unmanned aerial vehicle (UAV) technologies combined with digital image processing have recently been applied to crack assessment to overcome the drawbacks of manual visual inspection. However, identification of crack information in terms of width and length has not been fully explored in the UAV-based applications, because of the absence of distance measurement and tailored image processing. This paper presents a crack identification strategy that combines hybrid image processing with UAV technology. Equipped with a camera, an ultrasonic displacement sensor, and a WiFi module, the system provides the image of cracks and the associated working distance from a target structure on demand. The obtained information is subsequently processed by hybrid image binarization to estimate the crack width accurately while minimizing the loss of the crack length information. The proposed system has shown to successfully measure cracks thicker than 0.1 mm with the maximum length estimation error of 7.3%.<\/jats:p>","DOI":"10.3390\/s17092052","type":"journal-article","created":{"date-parts":[[2017,9,7]],"date-time":"2017-09-07T13:59:10Z","timestamp":1504792750000},"page":"2052","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":194,"title":["Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3838-4153","authenticated-orcid":false,"given":"Hyunjun","family":"Kim","sequence":"first","affiliation":[{"name":"School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Korea"}]},{"given":"Junhwa","family":"Lee","sequence":"additional","affiliation":[{"name":"School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Korea"}]},{"given":"Eunjong","family":"Ahn","sequence":"additional","affiliation":[{"name":"School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Korea"}]},{"given":"Soojin","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, University of Seoul, Seoul 02504, Korea"}]},{"given":"Myoungsu","family":"Shin","sequence":"additional","affiliation":[{"name":"School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7737-1892","authenticated-orcid":false,"given":"Sung-Han","family":"Sim","sequence":"additional","affiliation":[{"name":"School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2017,9,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.isprsjprs.2014.02.013","article-title":"Unmanned aerial systems for photogrammetry and remote sensing: A review","volume":"92","author":"Colomina","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12518-013-0120-x","article-title":"UAV for 3D mapping applications: A review","volume":"6","author":"Nex","year":"2014","journal-title":"Appl. Geomat."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Campos, I.S., Nascimento, E.R., Freitas, G.M., and Chaimowicz, L. (2016). A height estimation approach for terrain following flights from monocular vision. Sensors, 16.","DOI":"10.3390\/s16122071"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"160","DOI":"10.2174\/1872212110666160712230039","article-title":"State of technology review of civilian UAVs","volume":"10","author":"Chen","year":"2016","journal-title":"Recent Pat. Eng."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Gonzalez, L.F., Montes, G.A., Puig, E., Johnson, S., Mengersen, K., and Gaston, K.J. (2016). Unmanned Aerial Vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation. Sensors, 16.","DOI":"10.3390\/s16010097"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Sampedro, C., Bavle, H., Sanchez-Lopez, J.L., Fern\u00e1ndez, R.A.S., Rodr\u00edguez-Ramos, A., Molina, M., and Campoy, P. (2016, January 7\u201310). A flexible and dynamic mission planning architecture for UAV swarm coordination. Proceedings of the International Conference on Unmanned Aircraft Systems (ICUAS), Arlington, TX, USA.","DOI":"10.1109\/ICUAS.2016.7502669"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Vetrella, A.R., Fasano, G., Accardo, D., and Moccia, A. (2016). Differential GNSS and vision-based tracking to improve navigation performance in cooperative multi-UAV systems. Sensors, 16.","DOI":"10.3390\/s16122164"},{"key":"ref_8","first-page":"1183","article-title":"UAV for mapping\u2014Low altitude photogrammetric survey","volume":"37","author":"Zongjian","year":"2008","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_9","first-page":"25","article-title":"UAV photogrammetry for mapping and 3d modeling\u2013current status and future perspectives","volume":"38","author":"Remondino","year":"2011","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_10","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_11","doi-asserted-by":"crossref","unstructured":"Byrne, J., O\u2019Keeffe, E., Lennon, D., and Laefer, D.F. (2017). 3D Reconstructions using unstabilized video footage from an unmanned aerial vehicle. J. Imaging, 3.","DOI":"10.3390\/jimaging3020015"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1061\/(ASCE)CF.1943-5509.0000145","article-title":"Small-format aerial photography for highway-bridge monitoring","volume":"25","author":"Chen","year":"2011","journal-title":"J. Perform. Constr. Facil."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1111\/j.1467-8667.2011.00727.x","article-title":"An unmanned aerial vehicle-based imaging system for 3D measurement of unpaved road surface distresses1","volume":"27","author":"Zhang","year":"2012","journal-title":"Comput.-Aided Civ. Infrastruct. Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.measurement.2016.02.030","article-title":"Determining the limits of unmanned aerial photogrammetry for the evaluation of road runoff","volume":"85","author":"Bueno","year":"2016","journal-title":"Measurement"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Srinivasan, S., Latchman, H., Shea, J., Wong, T., and McNair, J. (2004, January 10\u201316). Airborne traffic surveillance systems: Video surveillance of highway traffic. Proceedings of the ACM 2nd International Workshop on Video Surveillance and Sensor Networks, New York, NY, USA.","DOI":"10.1145\/1026799.1026821"},{"key":"ref_16","unstructured":"Puri, A. (2005). A Survey of Unmanned Aerial Vehicles (UAV) for Traffic Surveillance, Department of Computer Science and Engineering, University of South Florida. Technical Report."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Heintz, F., Rudol, P., and Doherty, P. (2007, January 9\u201312). From images to traffic behavior-a uav tracking and monitoring application. Proceedings of the 10th International Conference on Information Fusion, Quebec City, QC, Canada.","DOI":"10.1109\/ICIF.2007.4408103"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"125","DOI":"10.5194\/isprsarchives-XL-1-W2-125-2013","article-title":"High-resolution multisensor infrastructure inspection with unmanned aircraft systems","volume":"1","author":"Eschmann","year":"2013","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Choi, S.-S., and Kim, E.-K. (2015, January 1\u20133). Building crack inspection using small UAV. Proceedings of the 17th International Conference on Advanced Communication Technology, PyeongChang, Korea.","DOI":"10.1109\/ICACT.2015.7224792"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.ifacol.2015.08.101","article-title":"Embedded image processing systems for automatic recognition of cracks using UAVs","volume":"48","author":"Pereira","year":"2015","journal-title":"IFAC-PapersOnLine"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"508","DOI":"10.1016\/j.procs.2015.06.058","article-title":"Health monitoring of civil structures with integrated UAV and image processing system","volume":"54","author":"Sankarasrinivasan","year":"2015","journal-title":"Procedia Comput. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1168","DOI":"10.1002\/stc.1831","article-title":"Bridge related damage quantification using unmanned aerial vehicle imagery","volume":"23","author":"Ellenberg","year":"2016","journal-title":"Struct. Control Health Monit."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1061\/(ASCE)0887-3801(2003)17:4(255)","article-title":"Analysis of edge-detection techniques for crack identification in bridges","volume":"17","author":"Abudayyeh","year":"2003","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1061\/(ASCE)0887-3801(2006)20:3(210)","article-title":"Improved image analysis for evaluating concrete damage","volume":"20","author":"Hutchinson","year":"2006","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Zhao, H., Qin, G., and Wang, X. (2010, January 16\u201318). Improvement of canny algorithm based on pavement edge detection. Proceedings of the 3rd International Congress on Image and Signal Processing, Yantai, China.","DOI":"10.1109\/CISP.2010.5646923"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"719","DOI":"10.12989\/sss.2014.14.4.719","article-title":"Automated assessment of cracks on concrete surfaces using adaptive digital image processing","volume":"14","author":"Liu","year":"2014","journal-title":"Smart Struct. Syst."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1061\/(ASCE)CP.1943-5487.0000446","article-title":"Concrete crack assessment using digital image processing and 3D scene reconstruction","volume":"30","author":"Liu","year":"2016","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.autcon.2005.02.007","article-title":"Segmentation of buried concrete pipe images","volume":"15","author":"Sinha","year":"2006","journal-title":"Autom. Constr."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1109\/TIP.2005.860311","article-title":"Digital image processing techniques for the detection and removal of cracks in digitized paintings","volume":"15","author":"Giakoumis","year":"2006","journal-title":"IEEE Trans. Image Process."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1111\/mice.12263","article-title":"Deep learning-based crack damage detection using convolutional neural networks","volume":"32","author":"Cha","year":"2017","journal-title":"Comput.-Aided Civ. Infrastruct. Eng."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1080\/15732470801945930","article-title":"A survey and evaluation of promising approaches for automatic image-based defect detection of bridge structures","volume":"5","author":"Jahanshahi","year":"2009","journal-title":"Struct. Infrastruct. Eng."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.cemconres.2017.04.018","article-title":"Comparative analysis of image binarization methods for crack identification in concrete structures","volume":"99","author":"Kim","year":"2017","journal-title":"Cem. Concr. Res."},{"key":"ref_33","unstructured":"Bernsen, J. (1986, January 27\u201331). Dynamic thresholding of grey-level images. Proceedings of the 8th International Conference on Pattern Recognition, Paris, France."},{"key":"ref_34","unstructured":"Niblack, W. (1986). An Introduction to Digital Image Processing, Prentice Hall. [1st ed.]."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/S0031-3203(99)00055-2","article-title":"Adaptive document image binarization","volume":"33","author":"Sauvola","year":"2000","journal-title":"Pattern Recognit."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1007\/s10044-003-0197-7","article-title":"Extraction and recognition of artificial text in multimedia documents","volume":"6","author":"Wolf","year":"2004","journal-title":"Pattern Anal. Appl."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Khurshid, K., Siddiqi, I., Faure, C., and Vincent, N. (2010, January 19\u201321). Comparison of Niblack inspired binarization methods for ancient documents. Proceedings of the 16th International Conference on Document Recognition and Retrieval, San Jose, CA, USA.","DOI":"10.1117\/12.805827"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"869","DOI":"10.1109\/34.161346","article-title":"Thinning methodologies\u2014A comprehensive survey","volume":"14","author":"Lam","year":"1992","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1109\/TPAMI.1986.4767851","article-title":"A computational approach to edge detection","volume":"6","author":"Canny","year":"1986","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_40","unstructured":"Kim, H., and Sim, S.-H. (2016, January 6\u20139). Concrete crack assessment using unmanned aerial vehicle. Proceedings of the 24th Australasian Conference on the Mechanics of Structures and Materials, Perth, Australia."},{"key":"ref_41","unstructured":"Bouguet, J.Y. (2017, August 11). Camera Calibration Toolbox for Matlab. Available online: http:\/\/www.vision.caltech.edu\/bouguetj\/calib_doc\/."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1061\/(ASCE)1076-0342(2010)16:2(129)","article-title":"Reliability of crack detection methods for baseline condition assessments","volume":"16","author":"Laefer","year":"2010","journal-title":"J. Infrastruct. Syst."},{"key":"ref_43","unstructured":"ACI 224R-90 (1990). Control of Cracking in Concrete Structures, America Concrete Institute."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"025015","DOI":"10.1117\/1.JRS.11.025015","article-title":"Maximizing feature detection in aerial unmanned aerial vehicle datasets","volume":"11","author":"Byrne","year":"2017","journal-title":"J. Appl. Remote Sens."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/9\/2052\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:44:23Z","timestamp":1760208263000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/9\/2052"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,9,7]]},"references-count":44,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2017,9]]}},"alternative-id":["s17092052"],"URL":"https:\/\/doi.org\/10.3390\/s17092052","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,9,7]]}}}