基于LSD和FLD融合的道路裂缝图像预处理方法研究

Adaptive Road Crack Image Preprocessing Method Based on LSD-FLD Fusion

摘要:

针对道路中的路标、路沿等直线类干扰物影响道路裂缝识别的问题,提出一种基于LSD(Line Segment Detector)和FLD(Fast Line Detector)融合的道路裂缝图像预处理方法。首先,基于LSD算法和FLD算法对裂缝图像进行直线检测,获取直线类干扰物的线段坐标值；其次,根据直线检测算法返回的线段坐标值进行断线重连,解决了直线检测算法提取线段不连续的问题；最后,根据线段重连后获取的直线类干扰物的掩膜图和裂缝图像原图,运用FMM(Fast Marching Method)图像修复算法达到消除直线类干扰物的目的。经过大量实验分析可得:该方法能够有效地消除裂缝图像中的直线类干扰物,使得裂缝检测的准确率提升了7.1%。

Abstract:

This study proposes a road crack image preprocessing method based on the fusion of a line segment detector (LSD) and fast line detector (FLD) to address the issue of linear interference, such as road signs and road edges, which affect road crack recognition. First, based on the LSD and FLD algorithms, line detection is performed on the crack image to obtain the line segment coordinate values of linear interferences. Second, by reconnecting the broken lines based on the line segment coordinate values returned by the line detection algorithm, the problem of extracting discontinuous line segments is solved using the line detection algorithm. Finally, the fast marching method (FMM) inpainting algorithm is used to eliminate linear interferences using the mask image of the linear interferences and the original image of the crack image obtained after reconnecting the line segments. Based on extensive experimental analysis, this method can effectively eliminate linear interference in crack images, improving the accuracy of crack detection by 7.1%.