基于图像处理的道砟颗粒二维廓形追踪提取算法

获取道砟颗粒廓形是研究有砟轨道道床力学性能及开展仿真分析的基础。针对传统图像处理中利用边缘检测算法获得道砟二维廓形信息的不足,提出追踪提取算法。采用数码相机和计算机技术搭建图像采集平台,通过颜色空间转化、二值化处理、边界追踪和数据优化等步骤实现了道砟二维廓形的提取。算法特点在于,提取的道砟颗粒二维廓形数据为有序的点列,廓形曲线连续且闭合良好,检测出来的边缘是单像素宽,通过使用游标卡尺测量证明实际廓形的最大粒径在考虑测量误差及精度的条件下二者数值基本相同。同时,基于前期学者对棱角指数的算法对本文提取廓形进行相应计算并与实测值比较,数值基本吻合,从而说明本算法在一定误差及精度条件下的有效性与可靠性。

Algorithm Based on Image Processing for Tracing and Extracting 2D Contour of Railway Ballast

Extracting 2D contour of railway ballast is fundamental in the study and simulation analysis of ballast bed. Due to the shortage of traditional edge detection algorithms that are used to obtain 2D contour of ballast, the tracing and extracting algorithm is presented. Digital camera and computer are used to accomplish hardware construction, and the transformation of images' color space, binary processing, boundary tracing, data optimization and other procedures are employed to extract 2D contour of railway ballast. Features of the algorithm are that the extracted 2D contour data is a series of ordered dots, and the contour not only has good continuity and closeness, but also ensures single pixel wide of edge. The maximum particle size of real ballast is measured by Vernier caliper and compared with the maximum particle size of 2D contour. The two values are mostly equal to each other. At the same time, the extracted profile in this paper is calculated based on the algorithm of priori scholars on the angular exponent and compared with the measurement. The consistency of the values verifies the validity and reliability of this algorithm with allowable error and accuracy.