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Crack Detection on Asphalt Surface Image Using Enhanced Grid Cell Analysis

机译:利用增强电网分析沥青表面图像裂纹检测

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This paper presents image processing techniques based on grid cell analysis for crack detection on non-uniform illumination and strong texture images. The techniques are Grid Cell Analysis Chain and Cracked Cell Verification. Grid Cell Analysis Chain helps eliminate false detection of shadow border on an image as being a cracked line. Cracked Cell Verification helps eliminate false detection when a grid cell has some image noise or strong texture but does not really contain part of a cracked line. Good accuracy in finding cracked lines on a pavement image with non-uniform illumination and strong texture can be achieved with 13% and 21% of false positive and false negative respectively.
机译:本文介绍了基于网格电池分析的图像处理技术,用于对非均匀照明和强纹理图像的裂纹检测。该技术是网格细胞分析链和破裂的细胞验证。网格单元分析链有助于消除图像上的阴影边框的错误检测为裂纹线。破裂的细胞验证有助于消除当网格单元有一些图像噪声或强大的质地时消除错误检测,但并不真正包含裂纹线的一部分。在具有非均匀照明和强大质地的路面图像上找到裂纹线的良好准确性可以分别以13%和21%的假阳性和假阴性来实现。

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