Research and Application of Railway Turnout Gap Detection Based on Improved Canny Algorithm

Abstract

AbstractTurnout gap monitoring is research emphasis and hotspots of railway safety management. In order to solve the automation requirements of the turnout gap monitoring system, this paper proposes an automatic turnout gap detection algorithm based on image processing technology. After image preprocessing, an edge detection algorithm based on the Canny arithmetic operator is used to convert the image into an edge binary image, then look for all possible gaps. Then after screening, the real gap is preserved and marked. To solve the problem of low accuracy with complex environment, an improved Canny edge detection algorithm is proposed. The detection experimental results on images with different noises show that this method is better than traditional edge detection algorithm and get a high robustness in noisy environment. Meanwhile, this method can successfully eliminate the stripe noise.KeywordsCanny operatorEdge detectionTurnout gap monitoring