一种基于顶帽变换和Otsu阈值的轨道边缘提取方法  

Extraction of Railway Track Edge Based on Top Hat Transform and Otsu Thresholding

作　　者：李孟歆[1] 侯丁丁[1] 夏兴华[1] 许伟靖[1] 范静静[1] 

机构地区：[1]沈阳建筑大学,沈阳110168

出　　处：《集成技术》2013年第6期51-53,共3页Journal of Integration Technology

摘　　要：为了解决轨道障碍物识别中轨道边缘不易定位的问题,针对轨道图像的特征,文章提出了一种基于Otsu阈值改进的轨道边缘提取方法。该方法先确定铁轨主体的灰度区域,再通过Otsu求出灰度阈值,然后利用二值图像中标记连通区域,对轨道图像进行处理,得到清晰的轨道边缘提取图像。通过对几种已提出的并具有较好效果的边缘提取方法进行分析,如边缘梯度算子sobel、小波分割算法、Otsu自适应阈值分割等,并将其应用在实时轨道图像中,与改进的Otsu方法进行对比实验。结果表明,该方法实验效果准确、完整,并有效抑制了背景噪声。In order to locate the edge in the rail obstacle recognition, an improved algorithm for rail image’s edge extraction based on threshold segmentation with the features of rail images was proposed. Firstly, the main gray area of the rail was deifned, to ifnd the grayscale threshold through Otsu. The connected component in binary image was labeled so that clear edge image was extracted. Several edge extraction methods such as edge gradient operator sobel, wavelet segmentation algorithm, Otsu adaptive thresholding, were analyzed and applied in real-time rail image, and comparison experiments were conducted with that using the improved Otsu method. Experimental comparison results show that the experimental results by the improved method were more accurate and complete, with background noise being suppressed effectively.

关 键 词：OTSU 自适应阈值 边缘提取 二值化处理 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] U213.2[自动化与计算机技术—计算机科学与技术]