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• W4226252340 endingPage "126162" @default.
• W4226252340 startingPage "126162" @default.
• W4226252340 abstract "• Due to the complexity of pavement images, crack segmentation is the most challenging step in the automated inspection process. • The most common rule-driven-based and data-driven-based image segmentation algorithms are compared and discussed. • Strategies to obtain better results such as hybrid integration algorithms and optimization methods are presented. • Satisfactory image segmentation techniques for different types of pavement images are proposed. • Current challenges and future opportunities are presented to improve automatic pavement crack detection algorithms and make them applicable in practice. The prompt detection of early decay in the pavement could be an auspicious technique in road maintenance. Admittedly, early crack detection allows preventive measures to be taken to avoid damage and possible failure. With regards to the advancement in computer vision and image processing in civil engineering, traditional visual inspection has been replaced by semi-automatic/automatic techniques. The process of detecting objects from the images is a fundamental stage of any image processing technique since the accuracy rate of the classification will depend heavily on the quality of the results obtained from the segmentation step. The major challenge of pavement image segmentation is the detection of thin, irregular dark lines cracks that are buried into the textured backgrounds. Although the pioneering works on image processing methodologies have proven great merit of such techniques in detecting pavement surface distresses, there is still a need for further improvement. The academic community is already working on image-based identification of pavement cracks, but there is currently no standard structure. This literature review establishes the history of development and interpretation of existing studies before conducting new research; and focuses heavily on three major types of approaches in the field of image segmentation, namely thresholding-based, edge-based, and data driven-based methods. With comparison and analysis of various image segmentation algorithms, this research provides valuable information for researchers working on enhanced segmentation strategies that potentially yield a fully automated distress detection process for pavement images with varying conditions." @default.
• W4226252340 created "2022-05-05" @default.
• W4226252340 creator A5026463403 @default.
• W4226252340 creator A5044822857 @default.
• W4226252340 date "2022-02-01" @default.
• W4226252340 modified "2023-10-17" @default.
• W4226252340 title "A critical review and comparative study on image segmentation-based techniques for pavement crack detection" @default.
• W4226252340 cites W1513670756 @default.
• W4226252340 cites W1607537728 @default.
• W4226252340 cites W1644863801 @default.
• W4226252340 cites W1759600866 @default.
• W4226252340 cites W1963782251 @default.
• W4226252340 cites W1966619289 @default.
• W4226252340 cites W1967156832 @default.
• W4226252340 cites W1972544340 @default.
• W4226252340 cites W1976727107 @default.
• W4226252340 cites W1979622972 @default.
• W4226252340 cites W1982652168 @default.
• W4226252340 cites W1984153831 @default.
• W4226252340 cites W1995130521 @default.
• W4226252340 cites W1998239578 @default.
• W4226252340 cites W1999505076 @default.
• W4226252340 cites W2000779269 @default.
• W4226252340 cites W2010308265 @default.
• W4226252340 cites W2011122613 @default.
• W4226252340 cites W2017550618 @default.
• W4226252340 cites W2019496031 @default.
• W4226252340 cites W2021422668 @default.
• W4226252340 cites W2021893106 @default.
• W4226252340 cites W2022613107 @default.
• W4226252340 cites W2024168391 @default.
• W4226252340 cites W2025967950 @default.
• W4226252340 cites W2027091505 @default.
• W4226252340 cites W2027468584 @default.
• W4226252340 cites W2033849769 @default.
• W4226252340 cites W2035006112 @default.
• W4226252340 cites W2037718318 @default.
• W4226252340 cites W2040736875 @default.
• W4226252340 cites W2042616708 @default.
• W4226252340 cites W2049151613 @default.
• W4226252340 cites W2058988978 @default.
• W4226252340 cites W2059208457 @default.
• W4226252340 cites W2059713017 @default.
• W4226252340 cites W2075502112 @default.
• W4226252340 cites W2075631365 @default.
• W4226252340 cites W2075935813 @default.
• W4226252340 cites W2081857838 @default.
• W4226252340 cites W2083970667 @default.
• W4226252340 cites W2099967398 @default.
• W4226252340 cites W2104095591 @default.
• W4226252340 cites W2107941094 @default.
• W4226252340 cites W2128880484 @default.
• W4226252340 cites W2133059825 @default.
• W4226252340 cites W2134039617 @default.
• W4226252340 cites W2135427252 @default.
• W4226252340 cites W2141009477 @default.
• W4226252340 cites W2144494816 @default.
• W4226252340 cites W2151732551 @default.
• W4226252340 cites W2156035232 @default.
• W4226252340 cites W2183341477 @default.
• W4226252340 cites W2195180028 @default.
• W4226252340 cites W2329936231 @default.
• W4226252340 cites W2346804089 @default.
• W4226252340 cites W2474796106 @default.
• W4226252340 cites W2511065100 @default.
• W4226252340 cites W2519653196 @default.
• W4226252340 cites W2520959394 @default.
• W4226252340 cites W2560622558 @default.
• W4226252340 cites W2578773993 @default.
• W4226252340 cites W2748643398 @default.
• W4226252340 cites W2752900081 @default.
• W4226252340 cites W2757455114 @default.
• W4226252340 cites W2775977688 @default.
• W4226252340 cites W2785673697 @default.
• W4226252340 cites W2804144664 @default.
• W4226252340 cites W2808919226 @default.
• W4226252340 cites W2809991812 @default.
• W4226252340 cites W2810188946 @default.
• W4226252340 cites W2856215003 @default.
• W4226252340 cites W2884786778 @default.
• W4226252340 cites W2886369963 @default.
• W4226252340 cites W2889494142 @default.
• W4226252340 cites W2894490622 @default.
• W4226252340 cites W2896496331 @default.
• W4226252340 cites W2912530595 @default.
• W4226252340 cites W2939399833 @default.
• W4226252340 cites W2941356554 @default.
• W4226252340 cites W2946236343 @default.
• W4226252340 cites W2963125010 @default.
• W4226252340 cites W2964308596 @default.
• W4226252340 cites W2964350391 @default.
• W4226252340 cites W2965516370 @default.
• W4226252340 cites W2994406669 @default.
• W4226252340 cites W3005498204 @default.
• W4226252340 cites W3009158303 @default.
• W4226252340 cites W3011233732 @default.
• W4226252340 cites W3021470593 @default.
• W4226252340 cites W3105421998 @default.

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