无人机影像GrabCut路面裂缝识别  

Pavement cracks recognition by using UAV image based on GrabCut method

作　　者：武广臣[1] 刘艳[1] WU Guangchen;LIU Yan(Liaoning Institute of Science and Technology,Benxi 117004,China)

机构地区：[1]辽宁科技学院,辽宁本溪117004

出　　处：《测绘通报》2024年第8期90-95,共6页Bulletin of Surveying and Mapping

基　　金：国家自然科学基金(42071343);2022年度辽宁省教育厅基本科研项目(LJKFZ20220284)。

摘　　要：无人机影像裂缝提取是近年来研究的热点问题之一。针对无人机影像强边缘信息干扰问题,本文提出了一种基于GrabCut算子的裂缝识别方法。该方法首先运用GrabCut算子提取保留裂缝的前景路面,然后运用去噪、边缘检测和双阈值轮廓识别方法探测路面裂缝。这种裂缝识别方法较好地排除了大量伪边缘信息和次生噪声干扰,实现了高分辨率无人机影像裂缝自动识别。试验结果表明,基于GrabCut算子的路面提取方法优于颜色特征提取算法和分水岭算法,适用于复杂场景路面提取,具有较高的普适性;同时,该方法可以快速获取裂缝信息,检测尺度可以人为控制,易于实现多尺度裂缝信息识别。研究结果可应用于路面裂缝定位识别、线性路面设施检测及路面灾害性评估等领域。The crack extraction by UAV images is one of the hot issues in recent years,for the problem of strong edge information interference of UAV image,a crack recognition method based on GrabCut operator is proposed.Firstly,the method uses GrabCut operator to extract the foreground pavement with cracks,and then uses denoising,edge detection and double threshold contour recognition methods to detect pavement cracks.This method eliminates a lot of false edge information and secondary noise interference,and realizes automatic crack recognition of high resolution UAV image.The experimental results demonstrate that the road surface extraction method based on GrabCut operator is superior to color extraction algorithm and watershed algorithm,and it is suitable for road surface extraction in complex scene,it is with high universality.At the same time,the method proposed in this study can quickly obtain fracture information,the detection scale can be manually controlled,and it is easy to realize multi-scale fracture information recognition.The research results can be applied to pavement crack location and identification,linear pavement facility detection,pavement disaster assessment and other fields.

关 键 词：GrabCut算子 分水岭算法 高斯混合模型 计算机视觉 CANNY边缘检测 

分 类 号：P23[天文地球—摄影测量与遥感]