计算机科学 ›› 2019, Vol. 46 ›› Issue (6A): 208-210.

• 模式识别与图像处理 • 上一篇    下一篇

基于分数阶傅里叶变换的隧道低对比度裂缝检测

周丽军, 刘晓   

  1. 山西省交通科学研究院山西省公路智能监测工程技术研究中心 太原030000
  • 出版日期:2019-06-14 发布日期:2019-07-02
  • 作者简介:周丽军(1984-),女,博士,工程师,主要研究方向为路桥隧道检测,E-mail:zhoulj2012@hotmail.com;刘 晓(1986-),男,博士,高级工程师,主要研究方向为智能装备研发。
  • 基金资助:
    本文受国家自然科学基金项目(51705299),山西省交通运输厅科研项目(2017-1-25),山西省基础研究计划项目(201801D221047)资助。

Low-contrast Crack Detection Method Based on Fractional Fourier Transform

ZHOU Li-jun, LIU Xiao   

  1. Shanxi Engineering Research Center for Road Intelligent Monitoring,Shanxi Transportation Research Institute,Taiyuan 030000,China
  • Online:2019-06-14 Published:2019-07-02

摘要: 隧道结构与环境的复杂性,使得隧道裂缝的检测环境存在较多干扰,如混凝土泥浆、污渍、渗水的面积较大,与细小裂缝的对比度较低,利用常规的形态学方法很容易漏检裂缝。为解决此问题,提出一种基于分数阶傅里叶变换的裂缝检测方法。该方法通过分数阶傅里叶变换将裂缝图像映射到时频域空间,实现信号的时频域展开;同时不同阶次的分数阶傅里叶变换对应不同的时频域,有利于提取裂缝图像中的污渍特征,通过背景信息补偿污渍区域,均衡了图像背景的对比度;结合分数阶微积分方法对图像进行增强,最后利用连通域方法提取裂缝。实验结果表明,提出的方法能够有效去除隧道壁污渍,检测出低对比度的隧道裂缝。

关键词: 低对比度, 分数阶傅里叶变换, 裂缝检测, 图像增强

Abstract: Due to the complexity of tunnel structure and environment,strong interference exists in the detection environment of tunnel cracks,such as concrete mud,dirt,water seepage area,etc..This results in low contrast between background and small cracks.Therefore,it is easy to miss cracks by using conventional morphological methods.In order to solve this problem,this paper proposed a crack detection method based on fractional Fourier transform.In this me-thod,the image is mapped to different time-frequency domains by different order fractional Fourier transform,which is helpful to extract the filth feature in the crack image.The background contrast of the image is balanced by compensating the filth region with the background information.The fractional differential method is used to enhance the image and the connected domain method is used to extract the cracks.Experimental results show that the proposed method can effectively remove the filth region and detect tunnel cracks with low contrast.

Key words: Crack detection, Fractional fourier transform, Image enhance, Low-contrast

中图分类号: 

  • TP391.41
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