[1]边 琛,侯北平.基于典型裂纹的沥青路面视觉评估方法研究[J].浙江科技学院学报,2022,(03):242-250.[doi:10.3969/j.issn.1671-8798.2022.03.006 ]
 BIAN Chen,HOU Beiping.Research on visual assessment method of asphalt pavements based on typical cracks[J].,2022,(03):242-250.[doi:10.3969/j.issn.1671-8798.2022.03.006 ]
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基于典型裂纹的沥青路面视觉评估方法研究(/HTML)
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《浙江科技学院学报》[ISSN:1001-3733/CN:61-1062/R]

卷:
期数:
2022年03期
页码:
242-250
栏目:
出版日期:
2022-06-16

文章信息/Info

Title:
Research on visual assessment method of asphalt pavements based on typical cracks
文章编号:
1671-8798(2022)03-0242-09
作者:
边 琛侯北平
(浙江科技学院 自动化与电气工程学院,杭州 310023)
Author(s):
BIAN Chen HOU Beiping
(School of Automation and Electrical Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China)
关键词:
路面损坏评估 裂纹检测 图像分割 骨架提取 沥青路面
分类号:
TP391.41
DOI:
10.3969/j.issn.1671-8798.2022.03.006
文献标志码:
A
摘要:
针对现有沥青路面裂纹检测方法存在细小裂纹漏检、复杂裂纹检测精度低、自动化损坏评估准确度低等问题,提出了一种基于典型裂纹的沥青路面损坏视觉评估方法。首先,利用基于改进特征金字塔的ResNet网络对裂纹进行像素级检测; 其次,提取裂纹骨架信息,计算裂纹特征并判断裂纹类别; 最后,根据裂纹特征评估对应的损坏程度,结合裂纹类别和损坏程度,自动加权计算路面损坏状况指数。试验结果表明,采用本文方法检测沥青路面典型裂纹的准确率可达95.3%,而路面损坏评估相对误差仅1.6%。本算法能有效检测沥青路面典型裂纹,可为沥青路面自动化评估水平的提升提供参考。

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2021-07-09
基金项目:浙江省重点研发计划项目(2021C04030); 浙江省基础公益研究计划项目(LGG21F030004)
通信作者:侯北平(1976— ),男,山东省日照人,教授,博士,主要从事图像处理、机器视觉研究。E-mail:bphou@zust.edu.cn。
更新日期/Last Update: 2022-06-30