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高速公路路面裂缝识别算法研究
引用本文:马荣贵,;徐琨,;刘飞飞. 高速公路路面裂缝识别算法研究[J]. 交通信息与安全, 2014, 0(2): 90-94. DOI: 10.3963/j.issn.1674-4861.2014.02.018
作者姓名:马荣贵,  徐琨,  刘飞飞
作者单位:长安大学信息工程学院 西安710064
基金项目:交通运输部科技项目(批准号:201231849A70)、中央高校基金项目(批准号:CHD2010JC110)资助
摘    要:经过研究给出了不均匀光照的路面裂缝图像识别的详细算法。算法采用多窗口中值滤波进行图像平滑,既能去除图像的噪声点,又较好地保留了裂缝的边缘信息;使用背景子集图像插值校正法进行灰度校正,有效地克服了不均匀成像对后期图像分割的影响;采用otsu阈值分割、形态学去噪及连通区域标记完成裂缝图像分割;选用连通区域个数、投影特征和分布密度3个参数完成裂缝分类;最后提取裂缝长度、宽度和破损面积等裂缝参数。实验结果显示分类准确率为94%,线状裂缝长度误差均值为7.2%,宽度误差均值为11.3%,非线状裂缝的面积误差均值为9.6%,表明这一方法有效、可靠。 

关 键 词:裂缝检测   灰度矫正   图像分割   参数计算

Highway Surface Crack Image Identifying Algorithm
Affiliation:MA Ronggui, XU Kun, LIU Feifei (1. School of Information Engineering , Chag'an University, Xi'an 710064,China; 2. Shaanxi Province Road Traffic Intelligence Test and Equipment Engineering Technology Research Center, Xi'an 710064, China)
Abstract:An algorithm to automatically detect and classify pavement cracks is presented in this paper .First ,the multi-window median filter is used ,which can not only remove the noises but also reserve crack information .Second ,the background subset interpolation method is applied to dealing with non-uniform illumination in the post-segmentation step . After that ,the otsu threshold segmentation method ,morphologic method ,and connected components marking method are used sequentially to segment the crack image .Furthermore ,the number of connected components ,projection feature , and distribution density are selected to classify the cracks .Finally ,the main parameters for crack ,such as length ,width , and area ,etc .,are calculated .The results show that the classification can be as accurate as 94% ,with the crack's length error of 7 .2% ,width error of 11 .3% ,and area error of 9 .6% ,which demonstrates that the mehod is effective and relia-ble .
Keywords:crack detection  gray adjustment  image segmentation  parameter calculation
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