中文核心期刊
CSCD来源期刊
中国科技核心期刊
RCCSE中国核心学术期刊

重庆交通大学学报(自然科学版) ›› 2014, Vol. 33 ›› Issue (5): 37-41.DOI: 10.3969/j.issn.1674-0696.2014.05.08

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基于立体视觉的桥梁裂缝自动检测系统研究

张开洪,罗林,颜禹   

  1. 重庆交通大学 信息科学与工程学院,重庆 400074
  • 收稿日期:2013-07-21 修回日期:2013-09-21 出版日期:2014-10-15 发布日期:2015-03-10
  • 作者简介:张开洪(1973—),男,四川犍为人,副教授,主要从事桥梁健康检测、传感器技术方面的研究。E-mail:916835287@qq.com。
  • 基金资助:
    国家自然科学基金项目(50805188);重庆市高校创新团队项目(KJTD201306);国家级大学生创新训练计划项目(201210618001)

Bridge Crack Automatic Detection System Based on Stereo Vision

Zhang Kaihong, Luo Lin, Yan Yu   

  1. School of Information Science & Engineering, Chongqing Jiaotong University, Chongqing 400074, China
  • Received:2013-07-21 Revised:2013-09-21 Online:2014-10-15 Published:2015-03-10

摘要: 桥梁裂缝是评价桥梁安全性的重要指标之一。针对传统人工测量桥梁裂缝存在的人为误差大、漏检率高和实时性差等缺点,结合数字图像处理技术,设计了基于立体视觉的桥梁裂缝自动检测系统。该系统通过标定摄像机,设置特征点和对桥梁图像进行预处理以获取特征点坐标,然后应用双目测距原理,测量桥梁裂缝的深度;并通过对二值化图像相关像素点的统计,计算出桥梁裂缝长度和宽度。实验数据表明该系统能够实时、在线、精确地测量桥梁裂缝的长度、宽度和深度。

关键词: 桥梁工程, 桥梁裂缝, 自动检测, 立体视觉

Abstract: Bridge crack is an important indicator for bridge safety evaluation. Aiming at the disadvantages of high error, high missing detection rate and poor real-time capability in the traditional detection method of bridge crack, the bridge crack automatic detection system based on stereo vision was designed, combining with the digital image processing technology. The system obtained the feature points’ coordinates through camera calibration, setting feature points and preprocessing the crack images, and then the binocular distance measurement principle was applied to measure the crack depth. Moreover, the length and width of the crack was calculated by the statistics of related binary image pixels. The experimental results show that the proposed system can accurately measure bridge crack’s length, width and depth online in real-time.

Key words: bridge engineering, bridge crack, automatic detection, stereo vision

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