基于曲率滤波和N-P准则的路面裂缝识别方法  

Pavement crack detection based on curvature filters and N-P criterion

作　　者：王墨川 何莉 胡成雪 陶健 张德津[3] WANG Mo-chuan;HE Li;HU Cheng-xue;TAO Jian;ZHANG De-jin(School of Electrical and Electronic Engineering,Hubei University of Technology,Wuhan 430068;School of Mechatronics and Control Engineering,Shenzhen University,Shenzhen 518060;Guandong Key Laboratory for Urban Informatics,Shenzhen University,Shenzhen 518060,China)

机构地区：[1]湖北工业大学电气与电子工程学院,湖北武汉430068 [2]深圳大学机电与控制工程学院,广东深圳518060 [3]深圳大学广东省城市空间信息工程重点实验室,广东深圳518060

出　　处：《计算机工程与科学》2022年第10期1822-1831,共10页Computer Engineering & Science

基　　金：国家重点研发计划(2019YFB2102703);广东省教育厅重点领域专项项目(2020ZDZX1052);深圳市科创委稳定支持计划(20200809215801001)。

摘　　要：针对沥青路面裂缝不连续问题,提出一种基于曲率滤波和N-P准则的裂缝识别方法。通过组合最小矩形切平面和最小三角切平面及修正正则能量项的改进型曲率滤波算法,消除随机噪声并平滑纹理。采取二次分割策略提取疑似裂缝目标和运用裂缝几何特性去除块状或点状噪声,实现裂缝定位和获取裂缝片段。在此基础上,融合裂缝片段的位置和方向信息,提出利用N-P准则连接裂缝片段的端点,从而获得完整裂缝数据。研究结果表明,提出的方法对横裂、纵裂、块裂及龟裂等裂缝都具有较好的检测效果和较高的检测精度,裂缝检测的完整性达到90.5%以上。In order to solve the problem of discontinuous detection of asphalt pavement crack,a crack detection method based on curvature filters and N-P criterion is proposed.Combined with the minimal rectangular and trigonometric tangent planes,an improved curvature filter based on the regular energy function is modified to eliminate the random noise and smooth the texture.The suspected crack targets are extracted by adopting a coarse-to-fine segmentation methodology and the geometric characteristics are applied to remove noises like blocks or spots to locate the crack and obtain the crack segments.On this basis,merged with the information of position and direction of the crack segments,the N-P criterion-based method is adopted to connect the endpoints of the crack segments and obtain the complete crack data.The results show that the proposed algorithm can effectively detect the cracks with high detection precision,such as transverse cracks,longitudinal cracks,block cracks and turtle cracks.The integrity of crack detection is more than 90.5%.

关 键 词：路面裂缝 曲率滤波 N-P准则 裂缝识别 裂缝连接 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]