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Fracture Segmentation

Authors: Roberto Emanuele Rizzo;

Fracture Segmentation

Abstract

Code to segment fracture from images The code first uses a small and large median filter to segment the voids, i.e. pores and fractures, in the image. The sizes of the two median filters should preferentially be: (1) small median filter, smaller than the pore size; and (2) large median filter, larger than fracture widths. The resulting filtered image is the binarised. Because we are interested only in the linear features, i.e. the fractures, using a ratio between the maximum axis length and the eccentricity values of the connected components, the code filters out the round-shaped features. The code saves coordinates of segmented fracture into a txt useful to the input the data into FracPaQ. The code reshapes the fracture coordinates save in the cell array , into a format readable by FracPaQ: each line in the .txt file correspond to a segmented fracture with pairs of xn - yn coordinates. The test image used here, "INPUT_IMAGE.tif" is a CT micrograph of a ceramics sample (kaolin matrix + quartz temper). Outputs images also attached. The main script calls two functions: (1) roseEqualArea.m --> which allows to plot equal area rose digrams of the fractures' trace angles This function has been written by Dr. David Healy (Univerisity of Aberdeen) and it's part of the FracPaQ toolbox (http://fracpaq.com/index.html) (2) RDPsimplify.m --> which, by using theRamer-Douglas-Peucker algorithm for curve semplification, reduces the number of vertices in the fracture traces according to a specified tolerance. This function has been written by Wolfgang Schwanghart on 13 July 2010

Related Organizations
Keywords

Rocks, Segmentation, Geology, FOS: Earth and related environmental sciences, Fractures

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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