Abstract

Fault inspection plays an important role in ensuring the safe operation of freight cars. With the development of computer vision technology, vision-based fault inspection has become one of the principal means of fault inspection. A coupler yoke is an important component of the train’s connection system, and if the bolt goes missing, it would cause the separation of the train from the coupler, resulting in a serious accident. In this paper, we propose an automatic image inspection system to inspect the faults in coupler yokes during the operation of a freight train. Images of the coupler are acquired and the inspection process is divided into two parts: the localization part and the recognition part. In the localization part, we combine the normalized gradient magnitude with the histogram of gradients on six orientations to form the “Multiple Dimension Features”, design a fast algorithm to compute the multi-resolution image features, and use a linear support vector machine to locate the position of the cou...

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