摘要Cracking is a typical kind of defect present in cement concrete bridges. Image-based bridge crack detection is a new technology for the lossless digital detection of bridge defects. An image-based method is proposed for recognizing and extracting the characteristic parameters of cracks on the bridge surface. Three main processes are aimed at resolving the interference of construction joints, sunlight, defacements, and vibration. First, the characteristics of cracks found in the acquired and de-noised bridge images are analyzed. Second, suspicious cracks are extracted using pixel gray-value comparison. Finally, false cracks are removed through the computed measurement of the connected domain, whereas true cracks are maintained. The qualities of the images are tested, and the results show that the proposed method exhibits robustness and efficiency in detecting bridge cracks.
Abstract：Cracking is a typical kind of defect present in cement concrete bridges. Image-based bridge crack detection is a new technology for the lossless digital detection of bridge defects. An image-based method is proposed for recognizing and extracting the characteristic parameters of cracks on the bridge surface. Three main processes are aimed at resolving the interference of construction joints, sunlight, defacements, and vibration. First, the characteristics of cracks found in the acquired and de-noised bridge images are analyzed. Second, suspicious cracks are extracted using pixel gray-value comparison. Finally, false cracks are removed through the computed measurement of the connected domain, whereas true cracks are maintained. The qualities of the images are tested, and the results show that the proposed method exhibits robustness and efficiency in detecting bridge cracks.
于泳波, 李万恒, 张劲泉, 聂建国. 基于图像连通域的桥梁裂缝提取方法研究[J]. Journal of Highway and Transportation Research and Development, 2013, 7(1): 34-37.
YU Yong-bo, LI Wan-heng, ZHANG Jin-quan, NIE Jian-guo. Bridge Crack Extraction Method Based on Image-connected Domain. Journal of Highway and Transportation Research and Development, 2013, 7(1): 34-37.
[1] JTGD62-2004, Code for Design of Highway Reinforced Concrete and Prestressed Concrete Bridges and Culverts[S].(in Chinese)
[2] JTG/T J22-2008, Specifications for Strengthening Design of Highway Bridges[S]. (in Chinese)
[3] CHU Jiangwei, CHU Xiumin, WANG Rongben, et al. Resaerch on sphalt Pavement Surface Distress Image feature Extraction Method[J]. Journal of Image and Graphics, 2003, 8A(10):1211-1217. (in Chinese)
[4] ZHA Xudong, WANG Wenqiang. The Testing Method of Crack Width for Continuously Reinforced Concrete Pavement Based on Image Processing Technology[J]. Journal of Changsha University of Science and Technology:Natural Science Edition, 2007, 4(1):13-17. (in Chinese)
[5] SUN Bocheng, QIU Yanjun. Pavement Crack Diseaes Recognition Based on Image Processing Algorithm[J]. Journal of Highway and Transportation, 2008, 25(2):64-68. (in Chinese)
[6] ZHANG Xiuhua, HONG Hanyu, HOU Jia, et al. Study on the Realtime Detecting Method for Pavement Crack Images[J]. Journal of Electronics Design Engineering, 2009, 17(6):36-37. (in Chinese)
[7] TEOMETE E, AMIN V R, CEYLAN H. Digital Image Processing for Pavement Distress Analyses[C]//Proceesdings of the 2005 Mid-Continent Transportation Research Symposium. Iowa:[s. n.], 2005:1-13.
[8] XU Bugao, HUANG Yaxiong. Development of Automatic Pavement Surface Distress Inspection System[R]. Austin:Center for Transportation Research, the University of Texas at Austin, 2005.
[9] CHENG H D, CHEN J R. Novel Approach to Pavement Cracking Detection Based on Ruzzy Set Theory[J]. Journal of Computing in Civil Engineering, ASCE, 1999, 13(4):270-280.
[10] GENG Fei, QIAN Chunxiang. Image Analysis Technique for Quantitative Testing and Evaluation of Plastic Shrinkage Cracks in Concrete[J]. Journal of Southeast University:Nature Science Edition, 2003, 33(6):773-776. (in Chinese)
[11] YIN Lan. Measurement and Analysis for Crack Characters of Concrete Surface Based on Digital Image Processing Technology[D]. Nanjing:Southeast University, 2006. (in Chinese)
[12] ZHANG Weifeng, LIU Meng, YANG Minghui. Bridge Cracks Detecting Technology Based on Digital Image Processing[J]. Modern Transportation Technology. 2008, (5):38-45. (in Chinese)
[1]
常柱刚, 王林凯, 夏飞龙. 基于CV NewMark-b法桥梁风致振动FSI数值模拟[J]. Journal of Highway and Transportation Research and Development, 2019, 13(2): 28-37.
2013, Vol. 7 
