高速公路路面裂缝识别算法研究

Highway Surface Crack Image Identifying Algorithm

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。

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＆#39;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 .