Research on Rail Surface Defect Inspection System


Article Preview

In order to realize the inspection of rail surface defects with high speed and high precision, an automatic detection system based on machine vision is presented. The hardware structure of the system consists of the mechanical system, control system and visual imaging system. The software structure using histogram threshold segmentation, multi-structural morphological edge detection and other image processing methods to detect and identify defects automatically, and also built the simulation rail detection platform. The experimental results show that the cracks, scars and other detects can be accurately detected and extracted in real time, and meet the requirement of the rail surface inspection.



Edited by:

Mohamed Othman




Y. Hu et al., "Research on Rail Surface Defect Inspection System", Applied Mechanics and Materials, Vols. 229-231, pp. 1389-1393, 2012

Online since:

November 2012




[1] Yan Jun-long, Zheng Xiao-xi, Li Tie-yuan. Research on surface disfigurement of arc segments ceramic magnet automatic detection system. Computer Engineering and Applications. 2009. 45 (36): 228-231.

[2] Xing Cang-ju, Wang Shou-jue, Deng Hao-jiang, Luo Yu-jin . A New Filtering Algorithm Based on Extremum and Median Value. Journal of Image and Graphics. 2001. 6(6): 533-536.

[3] Ma Yun, Wang He, Zhang Xiaoguang, Hu Xiaoqin, Zhang Tao: Algorithm for Welding Defect Detection of Ray Images Based on Mathematical Morphology. Computer Measurement & Control. 2010. 18(5): 1008-1013.

[4] Zeng Jie-xian, Gong Yong . Auto-adaptive threshold segmentation algorithm for image of solid propellants grains. Computer Engineering and Applications, 2008. 44(28): 98-100.

[5] Xu Zhigang, Zhao Xiangmo, Song Huansheng, Lei Tao, Wei Na. Asphalt pavement crack recognition algorithm based on histogram estimation and shape analysis. Chinese Journal of Scientific Instrument. 2010. 31(10): 2260-2265.

[6] Wang Qian-gian, Peng Zhong, Liu Li. An Adaptive Method of Image Segmentation. Transactions Of Beijing Institute Of Technology 2003. 23(4): 521-524.

[7] Zhong Hui, Wang Yaonan, Zhou Bowen, Ge Ji : Research on automatic visual inspection method and system for foreign substances in medicine transfusion liquid. Journal of Electronic Measurement and Instrument 2010, 24(2): 125-130.