摘要
针对道路裂缝进行检测并将其数据录入数据库是进行路面养护的基础,为避免传统人工检测时可能出现的误差大、妨碍交通等问题。本研究将车载CCD相机所获取的公路路面图像通过均值滤波变换、局部自适应的阈值分割、形态学去噪后识别提取图像路面裂缝区域,并通过骨骼提取算法及中心矢量线毛刺剔除与续接处理,提出一种基于光学图像的路面裂缝中心矢量线提取方法,实现了自动化获取可录入数据库的路面裂缝数据。
Road crack detection and data entry into the database is the basis of road maintenance,in order to avoid the traditional manual detection may appear in the error,traffic obstruction and other problems.This article will carry the CCD digital camera photography road surface images obtained by average filtering transformation,local adaptive threshold segmentation,morphological identification of pavement crack image area is extracted after denoising,and through the skeleton extraction algorithm and the center vector line burr remove the characters and treatment to put forward a set of a pavement crack based on the optical image vector line extraction method,It realizes automatic acquisition of pavement crack data which can be entered into database.
作者
陈中桥
Chen Zhongqiao(China Railway First Survey and Design Institute Group Co.,Ltd.,Xi'an,China)
出处
《科学技术创新》
2023年第8期165-168,共4页
Scientific and Technological Innovation
关键词
图像分割
形态学去噪
骨骼提取
毛刺剔除
image segmentation
morphological denoising
bone extraction
removal of burr
