基于Hough变换和Catmull-Rom样条曲线的钢轨检测算法

Rail Detection Algorithm Based on Hough Transform and Catmull-Rom Spline Curve

针对现有的钢轨检测算法中对于钢轨识别准确性不高的问题,提出一种基于Hough变换和Catmull-Rom样条曲线的钢轨检测算法。首先对图像进行降噪预处理,利用Canny边缘检测算法进行边缘检测,然后利用Hough变换检测直轨,根据直轨消失点确定轨道模型,最后针对弯轨利用等分窗口搜索弯轨特征点,对选取的特征点进行Catmull-Rom样条曲线拟合弯轨。实验表明,该算法不仅能够准确拟合钢轨曲线,而且具有较好的准确性和鲁棒性。

Focusing on the problem of low accuracy of the rail identification in the existing rail detection algorithm,this paper proposes an algorithm based on Hough transform and Catmull-Rom spline curve.Firstly,the image is denoised and pre-processed,and Canny edge detection algorithm is used for edge detection.Then Hough transform is used to detect the straight track,and the track model is determined according to the vanishing point of the straight track.Finally,the curved track is searched for the characteristic points of the curved track using the bifurcation window.The selected feature points are fitted with Catmull-Rom spline curve fitting curves.Experiments show that the algorithm not only can accurately fit the rail curve,but also displays good accuracy and robustness.