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Improved Pavement Distress Detection Based on Contourlet Transform and Multi-direction Morphological Structuring Elements

机译:基于Contourlet变换和多向形态结构元素的改进路面遇险检测

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Traditional methods for crack distress detection cannot capture the geometric information of images and tend to amplify noise. In order to solve this problem, an improved algorithm based on contourlet transform and multi-direction morphological structuring elements is proposed. The new algorithm decomposed image into approximation coefficients and detail coefficients. Morphological erode operations is used to distinguish noise form detail information according to dependencies of contourlet coefficients, then nonlinear mapping function is used to modify the contourlet coefficients. And the enhanced image is obtained by contourlet inverse transform. Compared with other traditional methods, the experimental results indicate that our method can effectively extract the edges of cracks and evidently decrease the influence of noises. Moreover, it can provide good image processing speed.
机译:裂纹遇险检测的传统方法不能捕获图像的几何信息,并倾向于放大噪声。为了解决这个问题,提出了一种基于Contourlet变换和多向形态结构元件的改进的算法。新算法将图像分解为近似系数和细节系数。形态磁腐蚀操作用于根据Contourlet系数的依赖性区分噪声形式细节信息,然后使用非线性映射函数来修改Contourlet系数。通过Contourlet逆变换获得增强的图像。与其他传统方法相比,实验结果表明,我们的方法可以有效地提取裂缝的边缘,显然降低了噪声的影响。此外,它可以提供良好的图像处理速度。

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