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This study proposes and verifies a computer vision\u2010based approach for automatically distinguishing patched and unpatched potholes. Using two\u2010dimensional images, patched and unpatched potholes may have similar shapes. Therefore, this study relies on image texture descriptors to delineate these two objects of interest. The texture descriptors of statistical measurement of color channels, the gray\u2010level cooccurrence matrix, and the local ternary pattern are used to extract texture information from image samples of asphalt pavement roads. To construct a classification model based on the extracted texture\u2010based dataset, this study proposes and validates an integration of the Support Vector Machine Classification (SVC) and the Forensic\u2010Based Investigation (FBI) metaheuristic. The SVC is used to generalize a classification boundary that separates the input data into two class labels of patched and unpatched potholes. To optimize the SVC performance, the FBI algorithm is utilized to fine\u2010tune the SVC hyperparameters. To establish the hybrid FBI\u2010SVC framework, an image dataset consisting of 600 samples has been collected. The experiment supported by the Wilcoxon signed\u2010rank test demonstrates that the proposed computer vision is highly suitable for the task of interest with a classification accuracy rate\u2009=\u200994.833%.<\/jats:p>","DOI":"10.1155\/2021\/3511375","type":"journal-article","created":{"date-parts":[[2021,9,6]],"date-time":"2021-09-06T19:50:40Z","timestamp":1630957840000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Computer Vision\u2010Based Patched and Unpatched Pothole Classification Using Machine Learning Approach Optimized by Forensic\u2010Based Investigation Metaheuristic"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9450-4637","authenticated-orcid":false,"given":"Nhat-Duc","family":"Hoang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9231-2129","authenticated-orcid":false,"given":"Thanh-Canh","family":"Huynh","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7788-9627","authenticated-orcid":false,"given":"Van-Duc","family":"Tran","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,9,6]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)IS.1943-555X.0000539"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.1061\/JPEODX.0000189"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1155\/2019\/5369532"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1155\/2019\/4302805"},{"key":"e_1_2_9_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2018.09.002"},{"key":"e_1_2_9_6_2","volume-title":"Road Traffic Injuries","author":"WHO","year":"2020"},{"key":"e_1_2_9_7_2","volume-title":"Traffic Accidents Claim 6,700 Lives this Year","author":"VNN","year":"2020"},{"key":"e_1_2_9_8_2","doi-asserted-by":"publisher","DOI":"10.1117\/1.2172917"},{"key":"e_1_2_9_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2010.08.079"},{"key":"e_1_2_9_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2011.01.002"},{"key":"e_1_2_9_11_2","volume-title":"Computing in Civil Engineering","author":"Jog G. 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