Development of Cracking Condition Assessment System for Concrete Bridge Decks Using Image Processing Techniques
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2022-01-31
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Edition:Final Report
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Abstract:Modern society requires a sustainable, robust, and serviceable infrastructure system to promote social welfare and boost economy. To support such an infrastructure system, an efficient health monitoring framework is needed which can promptly detect the presence of defects and perform associated rehabilitation and maintenance. In civil infrastructure, one of the most common types of defects is cracking, which evolves rapidly under the impacts of heavy traffic, aging of materials, and drastic environmental changes. In recent decades, computer vision-based automated crack detection methodologies have been developed and extensively applied by professionals and researchers. Nevertheless, a few issues and challenges existing in this type of methodology are yet to be systematically investigated and properly addressed. In this report, a cracking condition assessment system is developed by leveraging advanced sensing and computer vision technologies, to address the issues and concerns in computer vision-based crack detection and provide accurate and efficient crack detection performance under real-world complexities. Experimental results and discussions show that the proposed cracking condition assessment system is capable to properly address the issues under investigation and leads to improved and more robust crack detection performance than current image-based methodologies.
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