The detection of rail surface defects is an important part of railway daily inspection, according to the requirements\nof modern railway automatic detection technology on real-time detection and adaptability. This paper presents a\nmethod for real-time detection of rail surface defects based on machine vision. According to the basic principle of\nmachine vision, an image acquisition device equipped with LED auxiliary light source and shading box has been\ndesigned and the portable testing model is designed to carry on the field experiment. In view of the real-time\nrequirement, the method of extracting the target area from the original image is carried out without image preprocessing.\nThe surface defects of the rail are optimized based on morphological process and the characteristics of\nthe defects are obtained by tracking the direction chain code. It is demonstrated that the maximum positioning\ntime of this proposed method is 4.65 ms and its maximum positioning failure rate is 5%. The real-time detection\nspeed of this proposed method can reach 2 m/s, which can carry out real-time detection of artificial hand walking.\nThe time of processing each picture is up to 245.61 ms, which ensures the real-time performance of the portable\ntrack defect vision inspection system. To a certain extent, the system can replace manual inspection and carry out\nthe digital management of track defects.
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