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An Automatic Approach for Accurate Edge Detection of Concrete Crack Utilizing 2D Geometric Features of Crack

机译:利用裂缝的二维几何特征进行混凝土裂缝边缘自动检测的自动方法

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摘要

The automatic edge detection of cracks on concrete structures plays an important role in the damage assessment process for cracked structures. In this paper, we proposed an automatic method for accurate edge detection of concrete cracks from real 2D images of concrete surfaces containing noisy and unintended objects. In the 2D image of a damaged concrete surface, cracks are usually observed as tree-like topology dark objects of which the branches are line-like and have local symmetry across their center axes. We utilize these two geometric properties of cracks to detect crack edges and discriminate them with edges of other unintended objects. The novel automatic crack edge detection is composed of two sequential stages. In the first stage, cracks are enhanced by a novel phase symmetry-based crack enhancement filter (PSCEF) based on their symmetric and line-like properties while non-crack objects are removed. Estimated crack center-lines are then obtained by thresholding the filtered images and applying morphological thinning algorithm to the binary image. In the second stage, the estimated center lines of the detected cracks are fitted by cubic splines and the pixel intensity profiles in the directions perpendicular to the splines are used to determine the edge points. The edge points are linked together to form the desired continuous crack edges. Various experiments of real concrete crack images are used to demonstrate the excellent performance of the proposed method.
机译:混凝土结构裂缝的自动边缘检测在裂缝结构的损伤评估过程中起着重要作用。在本文中,我们提出了一种自动方法,该方法可从包含噪声和意外对象的混凝土表面的真实2D图像中准确检测混凝土裂缝的边缘。在损坏的混凝土表面的2D图像中,通常观察到裂缝为树状拓扑暗对象,其分支为线状并在其中心轴上具有局部对称性。我们利用裂纹的这两个几何特性来检测裂纹边缘,并将其与其他意外对象的边缘区分开。新颖的自动裂纹边缘检测包括两个连续的阶段。在第一阶段,基于非对称物体的裂纹对称性和线状特性,通过基于相位对称的新型裂纹增强滤波器(PSCEF)增强裂纹。然后,通过对滤波后的图像进行阈值处理并将形态学细化算法应用于二进制图像来获得估计的裂纹中心线。在第二阶段,通过三次样条拟合估计的裂缝的中心线,并使用垂直于样条方向的像素强度轮廓来确定边缘点。边缘点链接在一起以形成所需的连续裂纹边缘。实际混凝土裂缝图像的各种实验被用来证明该方法的优异性能。

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