Automatic quantification of crack patterns by image processing
Automatic quantification of crack patterns by image processing
复制标题
通过图像处理自动量化裂纹图案
DOI：
10.1016/j.cageo.2013.04.008
复制
发表时间：
2013-08-01
影响因子：
4.4
通讯作者：
Suo, Wen-Bin
中科院分区：
文献类型：
--
作者：
Liu, Chun;Tang, Chao-Sheng;Suo, Wen-Bin
提出了用图像处理技术对裂纹模式进行量化。在此基础上开发了“裂纹图像分析系统”(CIAS)软件。以土壤裂隙网络图像为例，说明了图像处理技术和计算机辅助诊断系统的操作方法。裂纹图像的量化包括以下三个步骤：图像分割、裂纹识别和测量。首先使用聚类分析方法将图像转换为二值图像，去除二值图像中的噪声，并对裂纹空间进行融合。然后，从二值图像中提取裂纹网络的中轴，从而识别节点和裂纹节段。最后，可以自动计算出裂隙网络的各种几何参数，如节点数、裂隙数、冻结面积、冻结周长、裂缝面积、宽度、长度和方向。操作中使用的阈值是通过聚类分析和其他创新方法来指定的。因此，可以对裂隙网络中的对象(节点、裂隙和土块)进行自动量化。该软件可用于研究土体裂隙形态和岩石裂隙的产生和发展。(C)2013爱思唯尔有限公司。保留所有权利。
Image processing technologies are proposed to quantify crack patterns. On the basis of the technologies, a software "Crack Image Analysis System" (CIAS) has been developed. An image of soil crack network is used as an example to illustrate the image processing technologies and the operations of the CIAS. The quantification of the crack image involves the following three steps: image segmentation, crack identification and measurement. First, the image is converted to a binary image using a cluster analysis method; noise in the binary image is removed; and crack spaces are fused. Then, the medial axis of the crack network is extracted from the binary image, with which nodes and crack segments can be identified. Finally, various geometric parameters of the crack network can be calculated automatically, such as node number, crack number, clod area, clod perimeter, crack area, width, length, and direction. The thresholds used in the operations are specified by cluster analysis and other innovative methods. As a result, the objects (nodes, cracks and clods) in the crack network can be quantified automatically. The software may be used to study the generation and development of soil crack patterns and rock fractures. (C) 2013 Elsevier Ltd. All rights reserved.