Paper
6 May 2024 High-speed railway concrete slab crack detection based on image semantic segmentation method
Tianxue Man, Jianwei Mao, Yongjun Lai, Weifang Sun
Author Affiliations +
Proceedings Volume 13107, Fourth International Conference on Sensors and Information Technology (ICSI 2024); 131071J (2024) https://doi.org/10.1117/12.3029231
Event: Fourth International Conference on Sensors and Information Technology (ICSI 2024), 2024, Xiamen, China
Abstract
Rapid and accurate detection of surface cracks on high-speed railway concrete slabs is of great significance for maintaining the safety and reliability of railway structures. However, existing crack detection methods suffer from segmentation insufficiency and weak anti-interference capabilities. In this paper, a novel automated detection method based on image semantic segmentation is proposed to achieve segmentation detection and quantitative analysis of surface cracks on high-speed railway concrete track slabs. First, the crack images are preprocessed to enhance the crack edge features through white balance and filtering. Then, an image-driven semantic segmentation network CBAM-U-Net is utilized for pixel-level crack detection on the sampled crack images. The network reduces the computational effort and improves the accuracy mainly by improving the ‘skip connection’ information interaction mechanism of the U-Net network and introducing CBAM blocks. Finally, by counting the pixel number of the segmentation area, the crack can be quantitatively evaluated. The experimental result demonstrates the effectiveness of the proposed method, with an average Dice coefficient of 73.35%. This method provides a new strategy for automated crack detection on high-speed railway concrete track slabs.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Tianxue Man, Jianwei Mao, Yongjun Lai, and Weifang Sun "High-speed railway concrete slab crack detection based on image semantic segmentation method", Proc. SPIE 13107, Fourth International Conference on Sensors and Information Technology (ICSI 2024), 131071J (6 May 2024); https://doi.org/10.1117/12.3029231
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KEYWORDS
Image segmentation

Semantics

Image processing

Convolution

Data acquisition

Education and training

Image enhancement

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