Steel rail surface defect image adaptive segmentation method

Abstract

The invention discloses a steel rail surface defect image adaptive segmentation method. The method comprises the following steps of S1, extracting a steel rail region by adopting a row grayscale mean successive summation method; S2, preprocessing a steel rail region image; S3, performing structure region and non-structure region division on the steel rail region image; S4, further distinguishing a defective region and a shadow region by utilizing a non-local feature of the image in the structure region; S5, adaptively building a background image model according to different features in the image; S6, performing image difference; and S7, performing dynamic threshold segmentation. The image is divided into the structure region and the non-structure region by utilizing image local information, the size of a pixel neighborhood window is adaptively adjusted by utilizing non-local information to calculate a mean, the accurate background image model is built, and the image difference and the dynamic threshold setting are performed, so that while a defective part of the image is highlighted, the influence of uneven illumination and steel rail surface reflection property on steel rail surface defect detection is effectively reduced, an ideal image segmentation effect is achieved, and the rail surface detection precision is ensured.

Description

technical field [0001] The invention belongs to the technical field of machine vision image processing, and relates to an image segmentation method, in particular to an adaptive segmentation method for rail surface defect images. Background technique [0002] With the rapid development of my country's railway transportation, the traffic density and load capacity continue to increase, which aggravates the deterioration of the rail surface. At the same time, the operating mileage is also continuously expanding, which poses new problems for the short-cycle detection of the line. As a very basic element in railway transportation, steel rail plays a vital role in the safety of railway operations; and in railway traffic accidents, nearly 1 / 3 of the accidents are caused by defects in steel rails. With the introduction of advanced production technology, the probability of defects inside the rails has been greatly reduced, and instead, rail surface defects lead to frequent rail frac...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the above-mentioned technical problems, the present invention provides a method for adaptive segmentation of rail surface defect images, which makes full use of the local and non-local information of the image, divides the image into structural and non-structural regions, and adaptively determines the size of the pixel neighborhood window to obtain Taking the average value to establish a background image model can effectively reduce the influence of uneven illumination and rail surface reflection characteristics on the detection of rail surface defects, so as to obtain an ideal image segmentation effect and ensure the accuracy of rail surface detection

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