基于Hough变换和Catmull-Rom样条曲线的钢轨检测算法
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摘要
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.
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.
引文
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[8]李阳腾龙,岑敏仪,白璇,等.高速铁路轨道检测的横向偏差算法研究[J].铁道学报,2016,38(8):119-126.
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[11]郭碧,董昱.基于分段曲线模型的铁路轨道检测算法[J].铁道科学与工程学报,2017,14(2):355-363.
[12]GONZALEZ R C,WOODS R E,EDDINS S L.Digital image processing using MATLAB[M].3rd ed.Beijing:Publishing House of Electronics Industry,2012:296-302.
[13]GONZALEZ R C,WOODS R E.Digital image processing[M].3rd ed.Beijing:Publishing House of Electronics Industry,2017:476-493.
[2]CATALANO A,BRUNO F A,GALLIANOC,et al.An optical fiber intrusion detection system for railway security[J].Sensors&Actuators:A Physical,2017(253):91-100.
[3]POTEKHIN A I,BRANISHTOV S,KUZNETSOV S.Discrete-event models of a railway network[J].Automation and Remote Control,2016,77(2):344-355.
[4]王忠立,蔡伯根.一种基于几何约束的轨道提取方法研究[J].交通运输系统工程与信息,2017(6):56-62,84.
[5]刘丽瑶,陈强,李艳娜,等.应用二阶Harris算子的高铁轨道近景影像特征点提取[J].测绘科学,2015,40(5):84-88.
[6]李睿,武晓春.基于数字图像处理的直线型铁轨的自动识别[J].电视技术,2014,38(3):167-169.
[7]居耀勇,陈黎.基于主方向迭代校正的铁轨检测算法[J].武汉科技大学学报,2012,35(6):473-477.
[8]李阳腾龙,岑敏仪,白璇,等.高速铁路轨道检测的横向偏差算法研究[J].铁道学报,2016,38(8):119-126.
[9]王前选,梁习锋,刘应龙,等.铁路钢轨视觉识别检测方法[J].中南大学学报:自然科学版,2014,45(7):2496-2502.
[10]HUANG Z P,HAN L,GONG GH.A local adaptive Catmull-Rom to reduce numerical dissipation of semi-Lagrangian advection[J].Computer Animation and Virtual Worlds,2015,26(2):141-146.
[11]郭碧,董昱.基于分段曲线模型的铁路轨道检测算法[J].铁道科学与工程学报,2017,14(2):355-363.
[12]GONZALEZ R C,WOODS R E,EDDINS S L.Digital image processing using MATLAB[M].3rd ed.Beijing:Publishing House of Electronics Industry,2012:296-302.
[13]GONZALEZ R C,WOODS R E.Digital image processing[M].3rd ed.Beijing:Publishing House of Electronics Industry,2017:476-493.