Real Time Detection of High Resolution Bridge Crack Image

Liu Xin-hong; Su Cheng-yue; Chen Jing; Xu Sheng; Luo Wen-jun; Li Yi-hong; Liu Ba

doi:10.12052/gdutxb.210038

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Real Time Detection of High Resolution Bridge Crack Image

更新时间：2026-05-27

- Real Time Detection of High Resolution Bridge Crack Image
- Vol. 39, Issue 6, Pages: 73-79(2022)
- 作者机构：
  
  广东工业大学物理与光电工程学院,广东,广州,510006
- 作者简介：
- 基金信息：
- DOI：10.12052/gdutxb.210038
  CLC： TP391
- Published：2022
- 稿件说明：
移动端阅览
刘信宏, 苏成悦, 陈静, 徐胜, 罗文骏, 李艺洪, 刘拔. 高分辨率桥梁裂缝图像实时检测[J]. 广东工业大学学报, 2022, 39(6): 73-79.

Liu Xin-hong, Su Cheng-yue, Chen Jing, et al. Real Time Detection of High Resolution Bridge Crack Image[J]. 2022, 39(6): 73-79.
刘信宏, 苏成悦, 陈静, 徐胜, 罗文骏, 李艺洪, 刘拔. 高分辨率桥梁裂缝图像实时检测[J]. 广东工业大学学报, 2022, 39(6): 73-79. DOI： 10.12052/gdutxb.210038.

Liu Xin-hong, Su Cheng-yue, Chen Jing, et al. Real Time Detection of High Resolution Bridge Crack Image[J]. 2022, 39(6): 73-79. DOI： 10.12052/gdutxb.210038.

摘要

针对现有桥梁裂缝检测算法实时性弱、可靠性差等问题，提出一种嵌入式平台上的实时检测算法。使用移动平均法粗分割，依据几何特征和区域生长法再分割，定位候选裂缝片段；基于裂缝先验条件，建立双判别准则的裂缝聚合模型，递归合并裂缝片段并抑制干扰。实验表明，算法能有效提取细小裂缝，抑制不均匀光照和污渍等复杂背景干扰，识别性能与数种现有算法相比提高115%以上；在嵌入式开发板上处理

1500

万像素的图像仅耗时1.73 s。

Abstract

The problem of current algorithms is lack of timeliness and reliability in bridge crack detection. In this paper

a real-time algorithm on embedded platform is proposed. Firstly

moving average method is used to segment the image coarsely. Then

candidate crack fragments are selected by region growing method using the geometric features of their contours. Finally

a crack merging model with two criteria is built to merge the crack fragments recursively and suppress interference

based on the prior condition of bridge cracks. Experimental results show that the proposed method performs better than several existing methods by 115% at least

especially on extracting hairline cracks and complex cases with uneven illumination and dirty mark. Dealing with an image with 15 megapixel on embedded platform

it costs only 1.73 s.

关键词

Keywords

references

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