Determination of the Fractal Dimension of the Fracture Network System Using Image Processing Technique

Fractal dimension (FD) is a critical parameter in the characterization of a rock fracture network system. This parameter represents the distribution pattern of fractures in rock media. Moreover, it can be used for the modeling of fracture networks when the spatial distribution of fractures is descri...

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Main Authors: Rouhollah Basirat, Kamran Goshtasbi, Morteza Ahmadi
Format: Article
Language:English
Published: MDPI AG 2019-04-01
Series:Fractal and Fractional
Subjects:
Online Access:https://www.mdpi.com/2504-3110/3/2/17
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spelling doaj-cc9f486982684403a80778b94caeeb6f2021-04-02T10:38:40ZengMDPI AGFractal and Fractional2504-31102019-04-01321710.3390/fractalfract3020017fractalfract3020017Determination of the Fractal Dimension of the Fracture Network System Using Image Processing TechniqueRouhollah Basirat0Kamran Goshtasbi1Morteza Ahmadi2Rock Mechanics Engineering Division, Faculty of Engineering, Tarbiat Modares University, 14115-111 Tehran, IranRock Mechanics Engineering Division, Faculty of Engineering, Tarbiat Modares University, 14115-111 Tehran, IranRock Mechanics Engineering Division, Faculty of Engineering, Tarbiat Modares University, 14115-111 Tehran, IranFractal dimension (FD) is a critical parameter in the characterization of a rock fracture network system. This parameter represents the distribution pattern of fractures in rock media. Moreover, it can be used for the modeling of fracture networks when the spatial distribution of fractures is described by the distribution of power law. The main objective of this research is to propose an automatic method to determine the rock mass FD in MATLAB using digital image processing techniques. This method not only accelerates analysis and reduces human error, but also eliminates the access limitation to a rock face. In the proposed method, the intensity of image brightness is corrected using the histogram equalization process and applying smoothing filters to the image followed by revealing the edges using the Canny edge detection algorithm. In the next step, FD is calculated in the program using the box-counting method, which is applied randomly to the pixels detected as fractures. This algorithm was implemented in different geological images to calculate their FDs. The FD of the images was determined using a simple Canny edge detection algorithm, a manual calculation method, and an indirect approach based on spectral decay rate. The results showed that the proposed method is a reliable and fast approach for calculating FD in fractured geological media.https://www.mdpi.com/2504-3110/3/2/17fractal dimensionfracture networkimage processingrock mass
collection DOAJ
language English
format Article
sources DOAJ
author Rouhollah Basirat
Kamran Goshtasbi
Morteza Ahmadi
spellingShingle Rouhollah Basirat
Kamran Goshtasbi
Morteza Ahmadi
Determination of the Fractal Dimension of the Fracture Network System Using Image Processing Technique
Fractal and Fractional
fractal dimension
fracture network
image processing
rock mass
author_facet Rouhollah Basirat
Kamran Goshtasbi
Morteza Ahmadi
author_sort Rouhollah Basirat
title Determination of the Fractal Dimension of the Fracture Network System Using Image Processing Technique
title_short Determination of the Fractal Dimension of the Fracture Network System Using Image Processing Technique
title_full Determination of the Fractal Dimension of the Fracture Network System Using Image Processing Technique
title_fullStr Determination of the Fractal Dimension of the Fracture Network System Using Image Processing Technique
title_full_unstemmed Determination of the Fractal Dimension of the Fracture Network System Using Image Processing Technique
title_sort determination of the fractal dimension of the fracture network system using image processing technique
publisher MDPI AG
series Fractal and Fractional
issn 2504-3110
publishDate 2019-04-01
description Fractal dimension (FD) is a critical parameter in the characterization of a rock fracture network system. This parameter represents the distribution pattern of fractures in rock media. Moreover, it can be used for the modeling of fracture networks when the spatial distribution of fractures is described by the distribution of power law. The main objective of this research is to propose an automatic method to determine the rock mass FD in MATLAB using digital image processing techniques. This method not only accelerates analysis and reduces human error, but also eliminates the access limitation to a rock face. In the proposed method, the intensity of image brightness is corrected using the histogram equalization process and applying smoothing filters to the image followed by revealing the edges using the Canny edge detection algorithm. In the next step, FD is calculated in the program using the box-counting method, which is applied randomly to the pixels detected as fractures. This algorithm was implemented in different geological images to calculate their FDs. The FD of the images was determined using a simple Canny edge detection algorithm, a manual calculation method, and an indirect approach based on spectral decay rate. The results showed that the proposed method is a reliable and fast approach for calculating FD in fractured geological media.
topic fractal dimension
fracture network
image processing
rock mass
url https://www.mdpi.com/2504-3110/3/2/17
work_keys_str_mv AT rouhollahbasirat determinationofthefractaldimensionofthefracturenetworksystemusingimageprocessingtechnique
AT kamrangoshtasbi determinationofthefractaldimensionofthefracturenetworksystemusingimageprocessingtechnique
AT mortezaahmadi determinationofthefractaldimensionofthefracturenetworksystemusingimageprocessingtechnique
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