Machine vision based mechanical appearance fault analysis and inspection is getting broad applications in past decades. Train wheel tread damage is a common fault pattern. The precedent step of the routine vision based analysis work is to get an image that includes the wheel surface. In this paper, a wheel curve edge extraction and object region segmentation framework is proposed. Firstly the salient rail line edge is extracted for a previous segmentation step and a sub image is acquired. Then line segment detector is used to detect the lines along the contours. And the wheel and shadow curve edge are approximated by line segments sets. Through certain geometry rules, the two edge lines are extracted. Finally the wheel object region is extracted perfectly and accurately.
With the rapid development of high-speed railway, the automated fault inspection is necessary to ensure train’s operation safety. Visual technology is paid more attention in trouble detection and maintenance. For a linear CCD camera, Image alignment is the first step in fault detection. To increase the speed of image processing, an improved scale invariant feature transform (SIFT) method is presented. The image is divided into multiple levels of different resolution. Then, we do not stop to extract the feature from the lowest resolution to the highest level until we get sufficient SIFT key points. At that level, the image is registered and aligned quickly. In the stage of inspection, we devote our efforts to finding the trouble of brake shoe, which is one of the key components in brake system on electrical multiple units train (EMU). Its pre-warning on wear limitation is very important in fault detection. In this paper, we propose an automatic inspection approach to detect the fault of brake shoe. Firstly, we use multi-resolution pyramid template matching technology to fast locate the brake shoe. Then, we employ Hough transform to detect the circles of bolts in brake region. Due to the rigid characteristic of structure, we can identify whether the brake shoe has a fault. The experiments demonstrate that the way we propose has a good performance, and can meet the need of practical applications.