一种新的路面裂缝自动检测算法

doi:10.16182/j.issn1004731x.joss.201709018

系统仿真学报 ›› 2017, Vol. 29 ›› Issue (9): 2009-2015.doi: 10.16182/j.issn1004731x.joss.201709018

一种新的路面裂缝自动检测算法

高尚兵^1*, 颉正¹, 潘志庚^1,2, 覃方哲¹, 李锐¹

1.淮阴工学院计算机与软件工程学院,淮安 223001;
2.杭州师范大学数字媒体与人机交互研究中心,杭州 311121

收稿日期:2017-04-28 发布日期:2020-06-02
作者简介:高尚兵(1981-),男,江苏淮安,博士,副教授,研究方向为图像处理、虚拟现实、模式识别。
基金资助:
国家自然科学基金(61402192,61332017),国家重点研发计划(2015BAK04B05),江苏省六大人才高峰资助项目(XYDXXJS-011),江苏省333工程资助项目(BRA2016454)

Novel Automatic Pavement Crack Detection Algorithm

Gao Shangbing^1*, Xie Zheng¹, Pan Zhigeng^1,2, Qin Fangzhe¹, Li Rui¹

1. College of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian 223001, China;
2. Virtual Reality and Human-computer Interaction Research Center, Hangzhou Normal University, Hangzhou 311121, China

Received:2017-04-28 Published:2020-06-02

摘要/Abstract

摘要： 实际路面图像因噪声成分复杂、覆盖面广,给检测裂缝造成难度。针对路面病害中裂缝图像自身的特征,提出了一种裂缝自动检测算法。该算法首先使用灰度矫正和滤波处理对裂缝图像进行预处理,然后结合最大类间方差法和Canny算子对病害图像进行边缘检测,再基于裂缝图像中裂缝的最大连通性提出了一种检测定位和精确分割算法,最后利用卷积神经网络算法对路面裂缝分类识别。实验结果表明,该方法在路面裂缝检测效率上具有更大的优势,而且对于不同类型的裂缝图像都具有鲁棒性。

关键词: 路面裂缝, 图像分割, 最大连通域, 卷积神经网络

Abstract: The complexity of noises covers a wide area of actual road images which causes that it is difficult to detect cracks. An automatic pavement crack detection algorithm was proposed in view of the characteristics of crack image in pavement disease. Gray-scale correction and filtering was used to preprocess the crack image. The maximum interclass variance method and Canny operator were used to detect the edge of the disease image, and then the localization and accurate segmentation algorithm was proposed for the crack image based on the maximum connectivity of the crack in the fracture image. The convolution neural network algorithm was used to recognize the pavement cracks. The experimental results show that the proposed method is superior to other advanced algorithms on the crack detection efficiency, and robust to the different types of crack images.

Key words: pavement cracks, image segmentation, maximum connected domains, convolution neural network

中图分类号:

TP391.4

高尚兵, 颉正, 潘志庚, 覃方哲, 李锐. 一种新的路面裂缝自动检测算法[J]. 系统仿真学报, 2017, 29(9): 2009-2015.

Gao Shangbing, Xie Zheng, Pan Zhigeng, Qin Fangzhe, Li Rui. Novel Automatic Pavement Crack Detection Algorithm[J]. Journal of System Simulation, 2017, 29(9): 2009-2015.

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一种新的路面裂缝自动检测算法

Novel Automatic Pavement Crack Detection Algorithm

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