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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">JWA</journal-id><journal-title-group><journal-title>Journal of World Architecture</journal-title></journal-title-group><issn>2208-3480</issn><eissn>2208-3499</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/jwa.v7i3.4826</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Research on Infrared Image Fusion Technology Based on Road Crack Detection</title><url>https://artdesignp.com/journal/JWA/7/3/10.26689/jwa.v7i3.4826</url><author>LiGuangjun,NanLin,ZhangLu,FengManman,LiuYan,MengXu</author><pub-date pub-type="publication-year"><year>2023</year></pub-date><volume>7</volume><issue>3</issue><history><date date-type="pub"><published-time>2023-06-28</published-time></date></history><abstract>This study aimed to propose road crack detection method based on infrared image fusion technology. By analyzing the characteristics of road crack images, this method uses a variety of infrared image fusion methods to process different types of images. The use of this method allows the detection of road cracks, which not only reduces the professional requirements for inspectors, but also improves the accuracy of road crack detection. Based on infrared image processing technology, on the basis of in-depth analysis of infrared image features, a road crack detection method is proposed, which can accurately identify the road crack location, direction, length, and other characteristic information. Experiments showed that this method has a good effect, and can meet the requirement of road crack detection.</abstract><keywords/></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>Zhao Y, Meng J, Yi R, 2022, Research on Real-Time Fusion Technology of Low-Light and Infrared Images Based on Artificial Intelligence. 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