Abstract
1-Introduction
2-Image Preprocessing of Concrete bridge Crack
3-The Edge Detection of Concrete Bridge Crack
4-Feature Data Extraction of Concrete Bridge Crack
5-Case analysis
6-Conclusion
Acknowledgements
Reference
Abstract
The appearance and development of cracks in the concrete bridge will seriously affect the safe use of bridge buildings. In order to better satisfy the crack detection requirement, this paper comes up with an image preprocessing scheme combining multiple adaptive filtering and contrast enhancement based on the image processing technology of concrete crack, which can improve the removal effect of background noise and obtain the characteristic vein information of tiny cracks. Then we designed a local adaptive algorithm of Otsu threshold segmentation and integrated with modified Sobel operator for removing isolated noise spots, so as to extract the crack edge information and improve the positioning accuracy of the crack boundary. Furthermore, according to the image feature of the bridge crack edge, the target crack is identified as well as classified and the feature data is calculated. The results of case analysis show that the data processing precision of the detection algorithm can reach 0.02mm, which can satisfy the actual engineering detection requirements of concrete bridge crack.
Introduction
In order to ensure the safe operation of a reinforced concrete bridge, it needs regular detection and timely maintenance, which concrete crack detection is one of the important items of bridge detection. And the digital image processing has become an important technology of concrete bridge detection, scholars have done a lot of research about the crack image detection technology, such as Yao et al. [1] design a climbing robot for bridge crack detection, as well as realize the identification and classification of the crack image. But the detection precision of the video image is not enough, and the application cannot be popularized in engineering practice. And for improving the transmission quality of image data, the terrestrial laser scanning (TLS)[2] technology processes and evaluates the crack images obtained by laser scanning. Liu et al. [3] optimized the robust processing effect of the crack image by using the method based on multi-scale morphological enhancement and crack characteristics on the concrete surface, but the image edge after morphological processing was prone to distortion.