一种基于纹理特征分析的地铁隧道裂缝检测方案

doi:10.16180/j.cnki.issn1007-7820.2022.11.006

电子科技 ›› 2022, Vol. 35 ›› Issue (11): 36-41.doi: 10.16180/j.cnki.issn1007-7820.2022.11.006

一种基于纹理特征分析的地铁隧道裂缝检测方案

张秋元¹,刘志全²

1.广州南方测绘科技股份有限公司广州分公司智能精密测量技术部,广东广州 510663
2.暨南大学网络空间安全学院,广东广州 510632

收稿日期:2021-04-25 出版日期:2022-11-15 发布日期:2022-11-11
作者简介:张秋元(1989-),女,初级工程师。研究方向:图像处理。|刘志全(1989-),男,博士,副教授。研究方向:智能交通、车联网、人工智能。
基金资助:
国家自然科学基金(61802146)

A Texture Feature Analysis-Based Crack Detection Scheme for Metro Tunnels

ZHANG Qiuyuan¹,LIU Zhiquan²

1. Intelligent Precision Measurement Technology Department,Guangzhou South Surveying and Mapping Technology Co. Ltd., Guangzhou 510663,China
2. College of Information Science and Technology,Jinan University,Guangzhou 510632,China

Received:2021-04-25 Online:2022-11-15 Published:2022-11-11
Supported by:
National Natural Science Foundation of China(61802146)

摘要/Abstract

摘要：

为实现地铁隧道智能巡检中裂缝病害的自动化检测,文中提出一种基于纹理特征分析的地铁隧道裂缝检测方案。首先对原始扫描图像采取腐蚀、对比度拉伸、加权邻域滤波等预处理以改善图像质量;然后对图像进行分块,并对分块区域采用改进的最大类间方差法来将裂缝从背景图像中分割出来;接着利用纹理特征分析滤除虚假裂缝信息,并进行图像细化以得到裂缝骨架图像;最终实现地铁隧道裂缝的自动化检测。实验结果表明,文中所提方案能够高效、准确地检测地铁隧道裂缝信息,并自动标识裂缝区域,检测效果优于现有方案。

关键词: 裂缝检测, 地铁隧道, 纹理特征分析, 自动化检测, 加权邻域滤波, 最大类间方差, 图像细化, 方向链码

Abstract:

To realize the automatic detection of cracks during the intelligent patrol in metro tunnels, this study presents a texture feature analysis-based crack detection scheme for metro tunnels. In the proposed scheme, several pre-processing operations such as erosion, contrast stretch and weighted neighborhood are firstly adopted to improve the quality of original scanned images. Then, the images are partitioned and the improved maximum between-cluster variance method is utilized for the partitioned areas so as to separate the cracks from the background images. Next, the texture feature analysis is leveraged to filter out incorrect crack information from the images. Afterwards, the images are thinned so as to obtain the corresponding skeleton images, and finally the automatic detection of cracks for metro tunnels can be realized. Furthermore, the experimental results demonstrate that the proposed scheme can efficiently and accurately detect the crack information for metro tunnels as well as automatically create labels for the crack areas, and the detection effect of the proposed scheme is significantly better than the existing schemes.

Key words: crack detection, metro tunnel, texture feature analysis, automatic detection, weighted neighborhood filter, OTSU, image thinning, direction chain code

中图分类号:

TP751.1

张秋元,刘志全. 一种基于纹理特征分析的地铁隧道裂缝检测方案[J]. 电子科技, 2022, 35(11): 36-41.

ZHANG Qiuyuan,LIU Zhiquan. A Texture Feature Analysis-Based Crack Detection Scheme for Metro Tunnels[J]. Electronic Science and Technology, 2022, 35(11): 36-41.

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一种基于纹理特征分析的地铁隧道裂缝检测方案

A Texture Feature Analysis-Based Crack Detection Scheme for Metro Tunnels

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