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Segmentation of cracks in X-ray CT images of tested macroporous plaster specimens

机译:测试的大孔石膏样品的X射线CT图像中的裂纹分割

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摘要

Precise segmentation of cracks is essential to characterize the structural properties of a rock specimen under compressive force. A two-dimensional internal cross-sectional image of rock can be created using X-ray computed tomography (CT scanning). Cracks in rocks usually have very poor local contrast which makes it difficult to detect and segment cracks from the background using existing popular edge detection algorithms. In this paper, we propose a two-dimensional matched filtering technique followed by local entropy based thresholding, morphological operators and length filtering to detect and segment cracks from the cross-sectional images of rock. The proposed algorithm is tested on several macroporous plaster specimens. Experimental results demonstrate the effectiveness and robustness of the algorithm compared to hand-labeled ground truth segmentations.
机译:裂纹的精确分割对于表征岩石样品在压缩力下的结构特性至关重要。可以使用X射线计算机断层扫描(CT扫描)创建岩石的二维内部横截面图像。岩石中的裂纹通常具有非常差的局部对比度,这使得使用现有流行的边缘检测算法很难从背景中检测和分割裂纹。在本文中,我们提出了一种二维匹配滤波技术,然后基于局部熵的阈值,形态学算子和长度滤波从岩石的横截面图像中检测和分割裂缝。该算法在几个大孔石膏标本上进行了测试。实验结果证明了与手标记的地面真相分割相比,该算法的有效性和鲁棒性。

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