Steel rail surface defect detection method based on reverse Gaussian difference

Abstract

The invention discloses a steel rail surface defect detection method based on reverse Gaussian difference. The method comprises the following steps that S1, acquiring a steel rail surface panoramic image through an image acquisition device; s2, extracting a steel rail image of a target area part from the steel rail surface panoramic image obtained in the step S1 by using a vertical projection method; s3, performing reverse Gaussian filtering on the steel rail image extracted in the step S2 to obtain a steel rail reverse Gaussian filtering image; s4, performing difference on the steel rail image extracted in the step S2 and the steel rail reverse Gaussian filtering image obtained in the step S3 to obtain a steel rail difference image; s5, binarizing the steel rail difference image in the step S4 to obtain a steel rail binarized image; and S6, carrying out area filtering and closing operation on the steel rail binary image in the step S5 so as to complete the detection of the defect areaon the surface of the steel rail. The method is suitable for various different rail environments, and a very good steel rail surface defect detection effect can be obtained.

Description

technical field [0001] The invention belongs to the technical field of machine vision detection, and in particular relates to a rail surface defect detection method based on reverse Gaussian difference. Background technique [0002] With economic growth, traffic congestion, environmental pollution and other issues, the demand for railway transportation has increased significantly, and at the same time, higher requirements have been put forward for modern railway infrastructure. Due to the characteristics of high density and heavy load of railways, the formation of rail surface defects, such as cracks, scars, peeling, etc., is accelerated. If they are not detected and treated in time, the rails may break and the train will derail. Therefore, how to improve the rail surface defect detection technology to meet the needs of modern rail detection systems is a major problem faced by countries all over the world. [0003] The traditional detection of railway track defects is done ...

AI Technical Summary

Problems solved by technology

[0005]1) Illumination conditions are easily affected by the track environment, seasons, and climate, which increases the difficulty of rail detection

[0006]2) Due to the special structure of the rail, its surface reflection is uneven, and shadow areas are easily generated, resulting in false defects

[0007]3) Rail surface defects are irregular in shape, irregular in distribution, and lack of defect characteristic information, making detection difficult

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