Binarization of road settlement monitoring point for autonomous rail rapid transit (ART) based on optimized Otsu algorithm

In order to more effectively extract the identification images of road settlement monitoring points of autonomous rail rapid transit (ART) from the actual complex scene, this paper proposes a binarization processing method based on the optimized Otsu algorithm. Firstly, the color-coded target image is converted into a grayscale image using the weighted average method to reduce the computational amount and improve the computational efficiency; secondly, Gaussian filtering is performed on the grayscale image to effectively remove the Gaussian noise in the image and improve the quality of the image; lastly, combining the morphology closure operation with the improved Otsu algorithm, the filtered image is binarized in order to eliminate the boundary effect and accurately extract the identification of monitoring point. The results show that the proposed method of this paper has higher stability and accuracy in processing the coded target images of road settlement monitoring point of ART.