Rail defect detection using Gabor filters with texture analysis

Railways is the major means of transport in most of the countries. Rails are the backbone of the track structure and should be protected from defects. Surface defects are irregularities in the rails caused due to the shear stresses between the rails and wheels of the trains. This type of defects should be detected to avoid rail fractures. The objective of this paper is to propose an innovative technique to detect the surface defect on rail heads. In order to identify the defects, it is essential to extract the rails from the background and further enhance the image for thresholding. The proposed method uses Binary Image Based Rail Extraction (BIBRE) algorithm to extract the rails from the background. The extracted rails are enhanced to achieve uniform background with the help of direct enhancement method. The direct enhancement method enhance the image by enhancing the brightness difference between objects and their backgrounds. The enhanced rail image uses Gabor filters to identify the defects from the rails. The Gabor filters maximizes the energy difference between defect and defect less surface. Thresholding is done based on the energy of the defects. From the thresholded image the defects are identified and a message box is generated when there is a presence of defects.