2022
DOI: 10.1155/2022/4992321
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A Depth Camera-Based Intelligent Method for Identifying and Quantifying Pavement Diseases

Abstract: In this study, a depth camera-based intelligence method is proposed. First, road damage images are collected and transformed into a training set. Then training, defect detection, defect extraction, and classification are performed. In addition, a YOLOv5 is used to create, train, validate, and test the label database. The method does not require a predetermined distance between the measurement target and the sensor; can be applied to moving scenes; and is important for the detection, classification, and quantif… Show more

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Cited by 2 publications
(1 citation statement)
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“…Based on the limitations of manual inspection and the advancements in computer technology, several researchers have proposed semiautomated defect detection algorithms that rely on computerassisted processing. These algorithms utilize image processing techniques, such as grayscale thresholding, edge detection, and wavelet transformation to accomplish the detection task [6][7][8][9]. This algorithm requires a large number of human resources and equipment to capture images and videos of road defects.…”
Section: Introductionmentioning
confidence: 99%
“…Based on the limitations of manual inspection and the advancements in computer technology, several researchers have proposed semiautomated defect detection algorithms that rely on computerassisted processing. These algorithms utilize image processing techniques, such as grayscale thresholding, edge detection, and wavelet transformation to accomplish the detection task [6][7][8][9]. This algorithm requires a large number of human resources and equipment to capture images and videos of road defects.…”
Section: Introductionmentioning
confidence: 99%