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9 October 2022 Concrete crack detection based on HED and k-means
YaFeng Zheng, RongDa Zhang, XueWei Tu, ChunYu Wang
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Proceedings Volume 12246, 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022); 122460Q (2022) https://doi.org/10.1117/12.2643505
Event: 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022), 2022, Qingdao, China
Abstract
Cracks are one of the early manifestations of concrete building diseases. Timely detection and repair of cracks is very important for building safety. In this paper, the holistically-nested edge detection(HED) network is applied to crack detection to realize the preliminary detection of concrete cracks. Compared with the traditional Canny operator, the cracks detected by HED are clearer. In view of the false detection caused by the interference of impurity areas when HED detects cracks, k-means algorithm is used to cluster and divide the HED detection results according to the pixel gray value, so as to obtain the cracks, background and impurity areas. The impurity area is modified into the background area to remove the impurity interference. Compared with the HED detection results, the precision of the detection results after k-means clustering is improved to 86.533%, and the recall rate is slightly reduced, but it is still as high as 88.791%.
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YaFeng Zheng, RongDa Zhang, XueWei Tu, and ChunYu Wang "Concrete crack detection based on HED and k-means", Proc. SPIE 12246, 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022), 122460Q (9 October 2022); https://doi.org/10.1117/12.2643505
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KEYWORDS
Detection and tracking algorithms
Convolution
Image processing
Image segmentation
Deconvolution
Edge detection
Feature extraction
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