期刊文献+

基于分形理论和二次分割的图像裂缝特征提取方法与应用 被引量:4

Method and application of image crack feature extraction based on fractal theory and secondary segmentation
在线阅读 下载PDF
导出
摘要 在役跨海桥梁、港口工程等的服役环境恶劣,多数情况下采集到的裂缝图像背景复杂、噪声干扰较多。为了克服现有技术存在的不足,提出一种基于分形理论和二次分割的图像裂缝特征提取方法。该方法采用分形参数作为裂缝图像的特征参数,能优先抑制裂缝图像中产生干扰过多的问题,有效克服灰度不均匀、噪声块多和背景复杂的干扰因素,同时基于二次分割理论,结合两种不同的算法特点,利用粗分割排除干扰区域,利用细分割对目标区域内裂缝精准分割,实现混凝土结构裂缝目标准确有效的提取,具有更好的分割效果。 Due to the bad service environment of sea-crossing bridge and port engineering,the crack images collected in most cases have complex background and high noise.A method of extracting image cracks feature based on fractal theory and secondary segmentation is proposed in this paper to overcome the shortcomings of the existing technology.In this method,fractal parameters are used as the characteristic parameters of the crack image,which can preferentially suppress the problem of excessive interference in the crack image,and effectively overcome the interference factors such as uneven gray level,large noise and complex background.At the same time,two different algorithms are combined based on the quadratic segmentation theory.The first segmentation is used to eliminate the interference area,and the second segmentation is used to precisely segment the cracks in the target area,so as to accurately and effectively extract the cracks of concrete structure and achieve better segmentation effect.
作者 李嘉民 应宗权 杨帅 刘梅梅 王翔 LI Jiamin;YING Zongquan;YANG Shuai;LIU Meimei;WANG Xiang(Key Laboratory of Hydraulic Structure Durability Technology for Transportation Industry,CCCC Fourth Harbor Engineering Institute Co.,Ltd.,Guangzhou 510230,China;Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai),Zhuhai 519082,China)
出处 《水运工程》 北大核心 2023年第4期166-173,共8页 Port & Waterway Engineering
关键词 结构监测 裂缝提取 分形 二次分割 图像增强 structure monitoring crack extraction fractal secondary segmentation image enhancement
  • 相关文献

参考文献7

二级参考文献55

共引文献156

同被引文献25

引证文献4

二级引证文献6

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部