Detect the rail track flaw by estimating the camera shaking

In this paper, we present a method of detecting the rail track bends and flaws. Different from the traditional machine-vision based methods which analyze the images of the rail surface, we estimate the shake of the camera - which is caused by the flaw or bend of the rail track - from the video used for railway environment surveillance. We provide both theoretical analysis - based on the theory of optical flow and passive navigation - and the corresponding fast algorithms, i.e. the brightness-pattern-matching code (BPMC) and shaking-type code (STC). Our method uses the surveillance video of the railway environment directly, thus, we do not need extra expensive instruments.