基于图像分析的路面裂缝检测识别研究

Research on Pavement Crack Detection and Recognition Based on Image Analysis

为了改善传统人工公路路面裂缝的检测效率与精度以及耗费大量人力物力,采用数字图像处理技术对公路路面裂缝进行检测识别。把采集到野外公路路面裂缝图像进行灰度化、灰度直方图均衡化、低帽滤波变换、滤波去噪、阈值分割操作检测识别出路面裂缝区域,提取线性裂缝提取骨架并求出其长度和最大最小宽度。通过使用MATLAB软件编制图像处理程序,验证本文提出的路面裂缝识别算法能够有效检测识别路面裂缝。

In order to improve the detection efficiency and accuracy of the traditional artificial highway pavement cracks,and consume a lot of manpower and material resources,the digital image processing technology is used to detect and identify the highway pavement cracks.The collected road surface crack images are processed by graying,gray histogram equalization,low hat filtering,filtering denoising and threshold segmentation to detect and identify the road surface crack area,extract the linear crack,extract the skeleton,and calculate its length and maximum and minimum width.By using MATLAB software to compile image processing program,it is verified that the pavement crack recognition algorithm proposed in this paper can effectively detect and recognize pavement cracks.