Abstract
Abstract
Bridge deck crack is the most serious bridge deck disease. To reduce the time, cost, and money cost of bridge deck crack detection, computer vision technology is combined with bridge deck crack detection. First of all, the main ways of obtaining bridge surface images are analyzed. Then, the algorithms of image enhancement, image noise reduction, image segmentation, crack extraction and recognition, and crack feature extraction in bridge deck crack detection based on computer vision are summarized respectively. Finally, the existing detection methods are reviewed, and the problems encountered in the research process and future research directions are further discussed.
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