scholarly journals Binary Images of Sheared Rock Joints: Characterization of Damaged Zones

1996 ◽  
Vol 7 (5-6) ◽  
pp. 521-526 ◽  
Author(s):  
Joëlle Riss ◽  
Sylvie Gentier ◽  
Katia Laffréchine ◽  
Rock Flamand ◽  
Guy Archambault
Keyword(s):  
Rock Joints ◽  
Binary Images

scholarly journals Laboratory characterization of rock joints

1994 ◽  
Author(s):  
S.M. Hsiung ◽  
D.D. Kana ◽  
M.P. Ahola ◽  
A.H. Chowdhury ◽  
A. Ghosh
Keyword(s):  
Rock Joints ◽  
Laboratory Characterization

scholarly journals Imaging of firn and bubbly ice in coaxial reflected light: a new technique for the characterization of these porous media

1998 ◽  
Vol 44 (147) ◽  
pp. 326-332 ◽  
Author(s):  
Laurent Arnaud ◽  
Michel Gay ◽  
Jean-Marc Barnola ◽  
Paul Duval
Keyword(s):  
Image Processing ◽  
Porous Media ◽  
Pore Network ◽  
New Technique ◽  
Binary Images ◽  
Reflected Light ◽  
A New Technique ◽  
Crystal Boundaries

AbstractA new technique for characterizing the structure of firn and bubbly ice is presented. This technique, based on observation of etched (sublimation) surfaces in coaxial reflected light, enables une to see simultaneously the pore network of the firn or bubbles in the ice and the crystal boundaries. At the same time, the main stages of image processing used to transform the initial photographs into clean binary images are described.

BINARY IMAGE REGISTRATION BASED ON GEOMETRIC MOMENTS: APPLICATION TO THE REGISTRAION OF 3D SEGMENTED CT HEAD IMAGES

2012 ◽  
Vol 12 (02) ◽  
pp. 1250009 ◽  
Author(s):  
GRIBAA NEJLA ◽  
NOBLET VINCENT ◽  
KHLIFA NAWRES ◽  
FAISAN SYLVAIN ◽  
HAMROUNI KAMEL
Keyword(s):  
Image Registration ◽  
Human Head ◽  
Binary Image ◽  
Registration Method ◽  
Binary Images ◽  
Matching Process ◽  
Geometric Moments ◽  
Ct Head ◽  
Scan Data

In this paper, we present a binary image registration strategy for the registration of segmented CT scan data of the human head. For the characterization of the 3D skull binary images we adopt a powerful representation of the binary images: the geometric moment invariants (GMIs). They provide pertinent and discriminant information related to the geometry of the binary objects, thereby leading to match points which have similar geometric properties, and also to enhance the quality of the matching process. For the registration algorithm we propose to use the topology-preserving B-spline-based registration method proposed by Noblet et al. for the registration of MRI head images. The algorithm has proven its efficiency and high registration precision. Since the information carried out by the different GMIs is complementary, we study and discuss the importance of combining various GMIs to better guide the matching process. Results obtained using synthetic deformation fields highlight the promising performance of the strategy.

Surface roughness characterization of open and closed rock joints in deep cores using X-ray computed tomography

2017 ◽  
Vol 98 ◽  
pp. 10-19 ◽  
Author(s):  
Melvin Diaz ◽  
Kwang Yeom Kim ◽  
Sun Yeom ◽  
Li Zhuang ◽  
Sehyeok Park ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Surface Roughness ◽  
Rock Joints ◽  
X Ray ◽  
X Ray Computed

MULTIFRACTAL ANALYSES OF GRAYSCALE AND BINARY SOIL THIN SECTION IMAGES

Fractals ◽  
2011 ◽  
Vol 19 (03) ◽  
pp. 299-309 ◽  
Author(s):  
H. ZHOU ◽  
E. PERFECT ◽  
Y. Z. LU ◽  
B. G. LI ◽  
X. H. PENG
Keyword(s):  
Pore Space ◽  
Depth Resolution ◽  
Geometrical Model ◽  
Partition Functions ◽  
Thin Sections ◽  
Binary Images ◽  
Multifractal Behavior ◽  
Generalized Dimensions ◽  
Grayscale Images

Multifractal analyses of binary images of soil thin sections (STS) are widely used to characterize pore structure. However, no geometrical model is known to exist for a binary multifractal. Thus, the multifractality of binary images, and the accuracy of multifractal parameters estimated from them, need to be carefully evaluated. We captured 8-bit depth resolution digital grayscale images of three STS images with dimensions of 1024 × 1024 pixels and a pixel length of 1.9 μm. Random grayscale geometrical multifractal fields (GMF) with similar dimensions and known multifractal parameters were constructed using generators extracted from the STS images. The STS and GMF grayscale images were objectively thresholded to give six binary images. The method of moments was used to compute the log-transformed partition function, log (χ(q, δ)) versus log(δ) where δ is box size, for each grayscale image and its binary counterpart. Consistent linearity was observed in the resulting functions for the grayscale images, indicating, by definition, multifractal behavior. In contrast, the log (χ(q, δ)) versus log(δ) plots for the binary images exhibited a two-region response, with a flat plateau at small scales and linearity at larger scales, indicating they were not true multifractals. Generalized dimensions (Dq) computed from the linear portions of the binary log-transformed partition functions were significantly over estimated for q ≪ 0 and underestimated for q ≫ 0 relative to corresponding Dq values for the grayscale images. Based on these results we contend that binary images are not mathematical multifractals, and that generalized dimensions estimated from them cannot be used to quantify pore space geometry. Instead we encourage further exploration of the use of grayscale images for multifractal characterization of soil structure. This direct approach is theoretically sound and does not require any intermediate thresholding step, which is known to influence the results of multifractal analyses.

scholarly journals Multiscale Research on Pore Structure Characteristics and Permeability Prediction of Sandstone

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
M. A. Shi-Jia ◽  
L. I. N. Yuan-Jian ◽  
L. I. U. Jiang-Feng ◽  
Kundwa Marie Judith ◽  
Ishimwe Hubert ◽  
...  
Keyword(s):  
Pore Structure ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Target Material ◽  
Future Research ◽  
Distribution Method ◽  
Binary Images ◽  
Permeability Prediction

The random existence of many irregular pore structures in geotechnical materials has a decisive influence on its permeability and other macroscopic properties. The analysis and characterization of the micropore structure of the material and its permeability are of great significance for geotechnical engineering. In this study, digital images with different magnifications were used to examine the pore structure and permeability of sandstone samples. The image processing method is used to obtain binary images, and then, the pore size distribution method is used to calculate the pore size distribution. Therefore, based on the Hagen-Poiseuille formula, we get the prediction value of material’s permeability and compare it with the value obtained from mercury intrusion porosimetry (MIP). It is found that different microscopic images with different magnification and various statistical methods of pore size have a specific influence on the characterization of pore structure and permeability prediction. The porosity of different magnifications is not the same, and the results obtained at higher magnifications are more consistent with the results obtained with MIP. With the increase of magnification, we can observe more pores in large sizes. The effect of CPSD (continuous pore size distribution) in pore size statistics is better than that of DPSD (discrete pore size distribution). In permeability prediction, the prediction result of higher magnification images are closer to the instrument test value, and the value of DPSD is more significant than that of CPSD. In future research, an appropriate method should be selected to obtain a reasonable prediction of the permeability of the target material.

scholarly journals An Experimental Microstructural Characterization of High-quality, Load-preserved Fabric 1-D Consolidated Kaolinite Samples

2019 ◽  
Vol 92 ◽  
pp. 01006
Author(s):  
Jun Kang Chow ◽  
Zhaofeng Li ◽  
Yu-Hsing Wang
Keyword(s):  
Microstructural Characterization ◽  
High Quality ◽  
Sem Images ◽  
Binary Images ◽  
Statistical Representation ◽  
Irregular Shapes ◽  
Printing Technique ◽  
Fabric Tensors ◽  
Sem Analyses

This paper describes a microstructural characterizations of high-quality, load-preserved fabric 1-D consolidated kaolinite samples, which covers from the beginning stage of clay sample preparation to the final stage of the microstructural analyses. To achieve this goal, a tailor-made oedometer is produced using the 3-D printing technique. First, a uniform kaolinite sample is prepared from a slurry state and then positioned into the 3-D printed oedometer for 1-D consolidation tests. Then, together with the applied loadings, the whole oedometer containing the consolidated kaolinite sample is submerged into the liquid nitrogen. This aims for preparing the dry sample by freeze drying, and at the same time, preserving the fabric associations for the subsequent microstructural characterizations. Afterwards, the sample is cut in half while frozen. An observation plane along the centre with the morphological information preserved is used for the scanning electron microscopy (SEM) analyses, and the remaining section is undergone the mercury intrusion porosimetry to obtain complementary information on the pore-size distribution. By ensuring the position and orientation of the SEM images taken, the number of SEM images, as well as the amount of particles and voids identified are maximized to enhance the statistical representation of the analysed results. In each sample, at least 3000 particles are identified, and the voids are segmented using proper binary images, of which their irregular shapes are further described using an equivalent ellipse. Fabric tensors are used to quantify the directional behaviour of the voids and particles. In addition, the shape evolution of the pores is examined to further understand the associated deformation mechanism. These comprehensive analyses provides quantitative evidences that the loading response of clay under 1-D consolidation is mainly governed by the inter-aggregate pores.

scholarly journals Characterization of rock joint surface anisotropy considering the contribution ratios of undulations in different directions

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Man Huang ◽  
Chenjie Hong ◽  
Chengrong Ma ◽  
Zhanyou Luo ◽  
Shigui Du
Keyword(s):  
Rock Joint ◽  
Weight Ratio ◽  
Rock Joints ◽  
Joint Surface ◽  
Orthogonal Direction ◽  
Natural Rock ◽  
Joint Surfaces ◽  
The Common ◽  
Joint Morphology

Abstract Anisotropy in rock joint is strongly dependent on undulating surface morphology. Recent research of the morphology showed the parameter can express the different types of anisotropic characteristics of the joint surface separately. This report aims to analyze the common characteristic of the anisotropic distribution and exhibit the anisotropic variation trend. The joint morphology function consists of two morphology functions of regular plane in orthogonal directions, and the anisotropic variation determined by the contribution ratios of the two morphology. The roughness weight ratio in orthogonal direction of joint surface is used as an index to describe the anisotropic variation behavior, which proposes the anisotropic variation coefficient (AVC). On this basis, it is divided into 5 levels from strong anisotropic to isotropic. According to the assumption of anisotropic arc distribution, the anisotropic analytic function is derived and the agreement between the deduced curves and measured data therefore suggests the possibility of defining the morphology anisotropy through the index AVC. Finally, we verify the characteristic of three natural rock joints, and prove the proposed function can reflect the anisotropic distribution trend. The new index can be used to describe the anisotropic variation behaviour of rock joint surfaces.

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