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An automated vision system that accurately measures the thickness of a brake shoe for rolling stock is proposed. Images of the brake shoes are captured automatically while rolling stock is passing by an inspection station. Toward this goal, location of the brake shoe in the image has to be determined first because they are not the same in the captured images. Shadow regions between the brake shoes and wheels are utilized that are common in all captured images. The boundary of the shadow regions is modeled by an inverse polynomial, and the constrained curve fitting method is adopted. Then, two curves that correspond to the front and back of the brake shoe are determined using the initial curve and intensity change information. Finally, the thickness is calculated using the detected curves, and experimental results showed that the brake shoe thickness was measured with an accuracy of 0.654 mm.
Applications of Computer Vision (WACV), 2009 Workshop on
Date of Conference: 7-8 Dec. 2009