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An automated vision system that inspects brake shoes for rolling stock is proposed. The system consists of two modules, namely, one for image acquisition and another for image analysis. The first module is placed under the railway tracks and automatically captures the images of brake shoes using digital cameras as trains pass the module. The captured images and train information are then transferred into a database. Three specifications, namely, the thickness, any unbalanced wear on the brake shoes, and the distances between the brake shoes and the wheels are measured by the second image analysis module. Shadow regions between the brake shoes and the wheels are defined for detecting brake shoes and wheels. They are also utilized to model both the boundaries of brake shoes and wheels as part of a constrained curve-fitting problem. The measurements were made in terms of the distance between the fitted curves rather than the number of pixels in the image. Experimental results show that our system can measure all specifications of the brake shoes with high accuracy values.
Kim et al. (Thu,) studied this question.