{"id":1841,"date":"2026-04-28T18:11:06","date_gmt":"2026-04-28T18:11:06","guid":{"rendered":"https:\/\/sbia.org.br\/lnlm\/?page_id=1841"},"modified":"2026-04-28T18:34:20","modified_gmt":"2026-04-28T18:34:20","slug":"vol23-no2-art4","status":"publish","type":"page","link":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no2\/vol23-no2-art4\/","title":{"rendered":"A Deep Learning Model for Automated Crack Detection and Characterization on Building Elements"},"content":{"rendered":"<p>Leticia M. G. Morais <a href=\"https:\/\/orcid.org\/0009-0008-3836-3401\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Heitor C. Dantas, Paulo H. A. Bezerra <a href=\"https:\/\/orcid.org\/0009-0001-2063-9958\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Ana Cl\u00e1udia Souza Vidal de Negreiros <a href=\"https:\/\/orcid.org\/0000-0002-6003-5876\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a> &amp; Rosana C. B. Rego <a href=\"https:\/\/orcid.org\/0000-0001-5997-1221\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a><\/p>\n<p><strong>Abstract:<\/strong> Detecting civil construction defects, such as material deterioration and cracks on masonry or structural members, is crucial for building safety and durability. Among all defects, cracks &#8211; whether visible or hidden &#8211; are critical issues that can compromise the integrity of buildings, bridges, roads, and other infrastructure elements. Artificial intelligence (AI) approaches, such as deep learning algorithms, can assist in the early identification and characterization of cracks, facilitating preventative actions to avoid future problems. In this study, we explore the application of deep learning with image segmentation techniques for crack detection and characterization in civil construction elements. We implemented a residual neural network capable of detecting cracks either in isolation or by mapping their distribution across surfaces such as concrete, bricks, steel, and wood. Additionally, we integrated the segmentation model SAM to improve the precision of crack segmentation in images. Through simulations and comparative analysis, we evaluated the performance of the models in accurately identifying and delineating cracks in civil infrastructure. The proposed model achieved an accuracy of 100\\% and an intersection over union of 0.95. Despite these high-performance metrics, there remains room for error analysis to further refine the approach, particularly in complex or edge-case scenarios. These results demonstrate the efficacy of the proposed approach in achieving accurate crack detection.<\/p>\n<p><strong>Keywords:<\/strong> Deep learning, crack detection, artificial intelligence, civil engineering, image segmentation.<\/p>\n<p><strong>DOI code:<\/strong> <a href=\"http:\/\/dx.doi.org\/10.21528\/lnlm-vol23-no2-art4\">10.21528\/lnlm-vol23-no2-art4<\/a><\/p>\n<p><strong>PDF file:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2025\/12\/vol23-no2-art4.pdf\">vol23-no2-art4.pdf<\/a><\/p>\n<p><strong>BibTex file:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2025\/12\/vol23-no2-art4.bib\">vol23-no2-art4.bib<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Leticia M. G. Morais , Heitor C. Dantas, Paulo H. A. Bezerra , Ana Cl\u00e1udia Souza Vidal de Negreiros &amp; Rosana C. B. Rego Abstract: Detecting civil construction defects, such as material deterioration and cracks on masonry or structural members, <a href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no2\/vol23-no2-art4\/\" class=\"read-more\">Read More &#8230;<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":1811,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-1841","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>A Deep Learning Model for Automated Crack Detection and Characterization on Building Elements - Learning and NonLinear Models<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no2\/vol23-no2-art4\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"A Deep Learning Model for Automated Crack Detection and Characterization on Building Elements - Learning and NonLinear Models\" \/>\n<meta property=\"og:description\" content=\"Leticia M. G. Morais , Heitor C. Dantas, Paulo H. A. Bezerra , Ana Cl\u00e1udia Souza Vidal de Negreiros &amp; Rosana C. B. Rego Abstract: Detecting civil construction defects, such as material deterioration and cracks on masonry or structural members, Read More ...\" \/>\n<meta property=\"og:url\" content=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no2\/vol23-no2-art4\/\" \/>\n<meta property=\"og:site_name\" content=\"Learning and NonLinear Models\" \/>\n<meta property=\"article:modified_time\" content=\"2026-04-28T18:34:20+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. tempo de leitura\" \/>\n\t<meta name=\"twitter:data1\" content=\"3 minutos\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no2\/vol23-no2-art4\/\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no2\/vol23-no2-art4\/\",\"name\":\"A Deep Learning Model for Automated Crack Detection and Characterization on Building Elements - Learning and NonLinear Models\",\"isPartOf\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no2\/vol23-no2-art4\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no2\/vol23-no2-art4\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\",\"datePublished\":\"2026-04-28T18:11:06+00:00\",\"dateModified\":\"2026-04-28T18:34:20+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no2\/vol23-no2-art4\/#breadcrumb\"},\"inLanguage\":\"pt-BR\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no2\/vol23-no2-art4\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"pt-BR\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no2\/vol23-no2-art4\/#primaryimage\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\",\"contentUrl\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no2\/vol23-no2-art4\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Browse issues\",\"item\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Learning &#038; Nonlinear Models &#8211; L&#038;NLM &#8211; Volume 23 &#8211; N\u00famero 2\",\"item\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no2\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"A Deep Learning Model for Automated Crack Detection and Characterization on Building Elements\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#website\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/\",\"name\":\"Learning and NonLinear Models\",\"description\":\"\",\"publisher\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/sbia.org.br\/lnlm\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"pt-BR\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#organization\",\"name\":\"Learning and NonLinear Models\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"pt-BR\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2021\/07\/logo-lnlm.png\",\"contentUrl\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2021\/07\/logo-lnlm.png\",\"width\":398,\"height\":94,\"caption\":\"Learning and NonLinear Models\"},\"image\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#\/schema\/logo\/image\/\"}}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"A Deep Learning Model for Automated Crack Detection and Characterization on Building Elements - Learning and NonLinear Models","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol23-no2\/vol23-no2-art4\/","og_locale":"pt_BR","og_type":"article","og_title":"A Deep Learning Model for Automated Crack Detection and Characterization on Building Elements - Learning and NonLinear Models","og_description":"Leticia M. 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