Heavy rail surface defects detection based on the morphology of multi-scale and dual-structure elements

Abstract

The heavy rail surface defect detection is one of the most important steps in the production and test of heavy rail, which directly affect the overall quality of heavy rail production. According to the characteristics of heavy rail surface defects, uneven brightness and noise, the heavy rail surface defects are detected based on the mathematical morphology of multi-scale and dual-structure elements in this paper. Compared with the traditional edge detection operators, the results show that this method owns strong anti-noise performance, can detect the small defect edge accurately under noise, and the peak signal to noise ratio(PSNR) is 24.5dB in the condition of without reducing the detection speed. The results of detection are obvious superior to traditional operators.