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Wang Q.,Central South University | Liang X.,Central South University | Liu Y.,Hunan Creator Information Technologies Co. | Lu Z.,Central South University | Peng C.,Hunan Creator Information Technologies Co.
Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology) | Year: 2014

Based on the railway rail feature in the monitoring image, combined with the Radon transform idea, the Bresenham line detection algorithm was derived for the railway rail recognition detection, and the railway rail line detection implementation method was proposed. A recognition method for the railway rail based on the image processing was obtained. The field test verified the numeration effectiveness of the method. The results show that the two straight lines calculated by the railway rail recognition detection method accurately fall on the two railway rails in the monitor image, and the two railway rails equations are obtained in the image coordinates, which shows that the method can accurately identify and detect the railway rail in the monitoring image, and can provide the necessary support for accurately monitoring the sand, snow and other foreign matter invasion.


Wang Q.,Central South University | Liang X.,Central South University | Liu Y.,Hunan Creator Information Technologies Co. | Lu Z.,Central South University | Peng C.,Hunan Creator Information Technologies Co.
Zhongguo Tiedao Kexue/China Railway Science | Year: 2014

The invasion of slowly changing foreign matters like sand or snow accumulation to railway lines poses a great threat to railway operation safety. In terms of the possible oversights due to the manual monitoring in current railway video surveillance system, we proposed a new method for detecting the invasion of slowly changing foreign matters to railway lines based on machine vision inspection technology and affine geometry principle. This new detection system, which was composed of linear light source model, camera model, and the linkage model connecting the line laser machines and detection cameras, was established according to the given detection principle, detection process and technical solution. Meanwhile, the rail visual recognition detection algorithm and the foreign matter thickness detection algorithm were proposed on the basis of the Radon transformation. Results obtain from the field tests carried out on Lanzhou-Xinjiang Railway using this detection method show that this system can real-time distinguish well the railway line state when trains passing or slowly changing foreign matters invading and measure the thickness of the foreign matters all day long, realize automatic alarm and early warning when the thickness of foreign matter reaches threshold.

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