{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T20:38:37Z","timestamp":1769373517867,"version":"3.49.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643681344","type":"print"},{"value":"9781643681351","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,11,9]],"date-time":"2020-11-09T00:00:00Z","timestamp":1604880000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,11,9]]},"abstract":"<jats:p>Cracks are an important sign of distress of concrete bridges and may reduce their service life and safety. For the case where there are stains, peeling, scratches, and uneven illumination on the surface of concrete bridges, and where it is difficult to accurately detect complete cracks, this paper proposes a new method to connect the breaks in cracks by adaptive morphological dilation based on crack direction. Most of the existing crack image detection methods attempt to achieve high detection accuracy by increasing the algorithm complexity but sacrifice real-time detection efficiency. A multiple filtering method based on a few adaptive feature thresholds is proposed to filter non-cracks and obtain a clear crack image by analyzing the morphological characteristic differences between real cracks and noise and pseudo-cracks. The experimental results show that the proposed method can effectively improve the integrity of cracks, remove different noise and pseudo-cracks, without modeling, and has a higher detection accuracy and speed, which is suitable for practical engineering applications.<\/jats:p>","DOI":"10.3233\/faia200747","type":"book-chapter","created":{"date-parts":[[2020,11,10]],"date-time":"2020-11-10T19:21:22Z","timestamp":1605036082000},"source":"Crossref","is-referenced-by-count":1,"title":["A New Approach for the Detection of Concrete Cracks Based on Adaptive Morphological Filtering"],"prefix":"10.3233","author":[{"given":"Huan","family":"Hou","sequence":"first","affiliation":[{"name":"College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China"}]},{"given":"Weiguo","family":"Lin","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Fuzzy Systems and Data Mining VI"],"original-title":[],"link":[{"URL":"http:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA200747","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,10]],"date-time":"2020-11-10T19:21:23Z","timestamp":1605036083000},"score":1,"resource":{"primary":{"URL":"http:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA200747"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,9]]},"ISBN":["9781643681344","9781643681351"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia200747","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,9]]}}}