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The Crack Detection Algorithm of Pavement Image Based on Edge Information

机译:基于边缘信息的路面图像裂缝检测算法

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摘要

As the images of pavement cracks are affected by a large amount of complicated noises, such as uneven illumination and water stains, the detected cracks are discontinuous and the main body information at the edge of the cracks is easily lost. In order to solve the problem, a crack detection algorithm in pavement image based on edge information is proposed. Firstly, the image is pre-processed by the nonlinear gray-scale transform function and reconstruction filter to enhance the linear characteristic of the crack. At the same time, an adaptive thresholding method is designed to coarsely extract the cracks edge according to the gray-scale gradient feature and obtain the crack gradient information map. Secondly, the candidate edge points are obtained according to the gradient information, and the edge is detected based on the single pixel percolation processing, which is improved by using the local difference between pixels in the fixed region. Finally, complete crack is obtained by filling the crack edge. Experimental results show that the proposed method can accurately detect pavement cracks and preserve edge information.
机译:随着路面裂缝的图像受大量复杂噪声的影响,例如不均匀的照明和水污渍,检测到的裂缝是不连续的并且裂缝边缘处的主体信息很容易丢失。为了解决问题,提出了一种基于边缘信息的路面图像中的裂缝检测算法。首先,通过非线性灰度变换功能和重建滤波器预处理图像以增强裂缝的线性特性。同时,设计自适应阈值处理方法根据灰度梯度特征粗略地提取裂缝边缘,并获得裂缝梯度信息图。其次,根据梯度信息获得候选边缘点,并且基于单个像素渗透处理检测边缘,通过使用固定区域中的像素之间的局部差异来改善。最后,通过填充裂缝边缘来获得完全裂缝。实验结果表明,该方法可以准确地检测路面裂缝并保留边缘信息。

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