State measurement of isolating switch using cost fusion and smoothness prior based stereo matching

Abstract

To better monitor the state of isolating switches, an efficient binocular vision-based state measurement system is proposed in this article. Two optimal cameras are selected as the vision of our inspection system. Firstly, stereo calibration and distortion rectification are performed on acquired image pair. Secondly, to recover the three-dimensional information of switch, we propose a semi-global stereo matching method by using data- and structure-driven cost volume fusion and then optimizing raw disparity map with weighted- and edge discriminated-smoothness prior. Gradient content is enforced on the weight for suppressing small-weight-accumulation problem in weak-textured regions. Besides, Hough transform with feature constraints is implemented for removing the chaotic lines and extracting center line of the switch arm. Finally, based on the center line and corresponding disparity map of the switch arm, triangulation principle is used for calculating the true angle between the switch arm and insulator such that whether or not the isolating switch is fully closed can be detected. The experimental results demonstrate that the proposed stereo matching method can achieve good performance in Middlebury v.3 data set and switch images, and the system can precisely measure the state of switches.