scholarly journals A System of FORTRAN for Three-Dimensional Texture Analysis

Texture ◽  
1974 ◽  
Vol 1 (3) ◽  
pp. 201-203 ◽  
Author(s):  
J. Jura ◽  
J. Pospiech ◽  
H. J. Bunge
Keyword(s):  
Texture Analysis ◽  
Three Dimensional ◽  
Memory Space

A system of FORTRAN programmes is being described which allows most of the standard problems of three-dimensional texture analysis to be easily carried out. It requires about 25 K memory space and it may easily be enlarged by incorporating further subroutines.

scholarly journals A New Library Program for Texture Calculations

1977 ◽  
Vol 2 (4) ◽  
pp. 225-241 ◽  
Author(s):  
F. Wagner ◽  
C. Esling ◽  
R. Baro
Keyword(s):  
Texture Analysis ◽  
Computing Time ◽  
Three Dimensional ◽  
Great Precision ◽  
Memory Space ◽  
Pole Figures ◽  
Library Program ◽  
Short Time ◽  
And Storage ◽  
Good Agreement

A new library program which allows the calculation and storage of the numerical tables necessary for a three-dimensional texture analysis is proposed. Its main characteristics are:–possibility of selecting the values to be stored according to the desired microscopic and macroscopic symmetries as well as to the step of exploration of the pole figures;–possibility of choosing the quantity of information to be stored for obtaining, in the further three-dimensional analysis, a good agreement between the computing time and the memory space; and–great precision of the stored values and short time of calculation due to the use of new and optimized aigorithms.

The Method of Fundamental Solutions for Solving Exterior Axisymmetric Helmholtz Problems with High Wave-Number

2013 ◽  
Vol 5 (04) ◽  
pp. 477-493 ◽  
Author(s):  
Wen Chen ◽  
Ji Lin ◽  
C.S. Chen
Keyword(s):  
Large Scale ◽  
Three Dimensional ◽  
Matrix Decomposition ◽  
Coefficient Matrix ◽  
Fundamental Solutions ◽  
Method Of Fundamental Solutions ◽  
Wave Number ◽  
High Wave Number ◽  
Memory Space ◽  
High Wave

AbstractIn this paper, we investigate the method of fundamental solutions (MFS) for solving exterior Helmholtz problems with high wave-number in axisymmetric domains. Since the coefficient matrix in the linear system resulting from the MFS approximation has a block circulant structure, it can be solved by the matrix decomposition algorithm and fast Fourier transform for the fast computation of large-scale problems and meanwhile saving computer memory space. Several numerical examples are provided to demonstrate its applicability and efficacy in two and three dimensional domains.

3D Texture Analysis of Corpus Caliosum Based on MR Images Inpatients with Alzheimer’s Disease and Mild Cognitive Impairment

2014 ◽  
Vol 533 ◽  
pp. 415-420 ◽  
Author(s):  
Wei Fang Liu ◽  
Xu Wang ◽  
Hong Xia
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Corpus Callosum ◽  
Texture Analysis ◽  
Three Dimensional ◽  
Texture Features ◽  
Grey Level ◽  
Run Length ◽  
3D Texture ◽  
3D Texture Analysis

This study investigated three-dimensional (3D) texture as a possible diagnostic marker of Alzheimers disease (AD). Methods: T1-weighted MRI of 18 AD patients, 18 Mild Cognitive Impairment (MCI) patients and 18 normal controls (NC) were selected.3D Texture parameters of the corpus callosum,including contrast, inverse difference moment , entropy, short run emphasis, long run emphasis, grey level nonuniformity, run length nonuniformity and fraction were extracted from the gray level co-occurrence matrix and run length matrix. Finally statistic significance was tested among three groups, and the correlations between parameters and Mini-Mental State Examination (MMSE) scores were calculated. Results: The results showed that the 3D texture features had significant differences (p<0.05) among three groups except grey level nonuniformity and run length nonuniformity that the difference was not significant (p>0.05) between MCI and NC or AD and MCI , and they were correlated with MMSE scores.Conclusions: 3D texture analysis can reflect the pathological changes of corpus callosum in patients with AD and MCI, and it may be helpful to AD early diagnosis.

scholarly journals 3D immersive visualization of micro-computed tomography and XRD texture datasets

2019 ◽  
Vol 34 (2) ◽  
pp. 97-102
Author(s):  
M. A. Rodriguez ◽  
T. T. Amon ◽  
J. J. M. Griego ◽  
H. Brown-Shaklee ◽  
N. Green
Keyword(s):  
Computed Tomography ◽  
Texture Analysis ◽  
Mechanical Strain ◽  
Three Dimensional ◽  
Multidimensional Analysis ◽  
Micro Computed Tomography ◽  
X Ray ◽  
3D Data ◽  
Pole Figures ◽  
Ct Data

Advancements in computer technology have enabled three-dimensional (3D) reconstruction, data-stitching, and manipulation of 3D data obtained on X-ray imaging systems such as micro-computed tomography (μ-CT). Likewise, intuitive evaluation of these 3D datasets can be enhanced by recent advances in virtual reality (VR) hardware and software. Additionally, the generation, viewing, and manipulation of 3D X-ray diffraction datasets, such as pole figures employed for texture analysis, can also benefit from these advanced visualization techniques. We present newly-developed protocols for porting 3D data (as TIFF-stacks) into a Unity gaming software platform so that data may be toured, manipulated, and evaluated within a more-intuitive VR environment through the use of game-like controls and 3D headsets. We demonstrate this capability by rendering μ-CT data of a polymer dogbone test bar at various stages of in situ mechanical strain. An additional experiment is presented showing 3D XRD data collected on an aluminum test block with vias. These 3D XRD data for texture analysis (χ, ϕ, 2θ dimensions) enables the viewer to visually inspect 3D pole figures and detect the presence or absence of in-plane residual macrostrain. These two examples serve to illustrate the benefits of this new methodology for multidimensional analysis.

scholarly journals Three-Dimensional Texture Analysis After Bunge and Roe: Correspondence Between the Respective Mathematical Techniques

1982 ◽  
Vol 5 (2) ◽  
pp. 95-125 ◽  
Author(s):  
C. Esling ◽  
E. Bechler-Ferry ◽  
H. J. Bunge
Keyword(s):  
Harmonic Analysis ◽  
Texture Analysis ◽  
Series Expansion ◽  
Three Dimensional ◽  
Analysis Methods ◽  
Mathematical Techniques

Bunge's and Roe's three-dimensional texture analysis methods, although both founded on harmonic analysis, show some differences between the various mathematical techniques used.This paper establishes the correspondence relation between the respective mathematical techniques allowing one to compare works done in either variant. Taking the latest developments in three dimensional texture analysis into account, the correspondence relations hold for the odd degrees l as well as for the even ones.Finally numerical tables give the extension of the symmetry coefficients B:l4mμ (after Bunge) and R4nμl (after Roe) to all the degrees l of the series expansion, even and odd, including l = 34.

Bone texture analysis is correlated with three-dimensional microarchitecture and mechanical properties of trabecular bone in osteoporotic femurs

2012 ◽  
Vol 31 (1) ◽  
pp. 82-88 ◽  
Author(s):  
Thomas Le Corroller ◽  
Martine Pithioux ◽  
Fahmi Chaari ◽  
Benoît Rosa ◽  
Sébastien Parratte ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Trabecular Bone ◽  
Texture Analysis ◽  
Three Dimensional ◽  
Bone Texture Analysis

Integrated seismic texture segmentation and cluster analysis applied to channel delineation and chert reservoir characterization

Geophysics ◽  
2011 ◽  
Vol 76 (5) ◽  
pp. P11-P21 ◽  
Author(s):  
Marcilio Castro de Matos ◽  
Malleswar (Moe) Yenugu ◽  
Sipuikinene Miguel Angelo ◽  
Kurt J. Marfurt
Keyword(s):  
Texture Analysis ◽  
Reservoir Characterization ◽  
Three Dimensional ◽  
Seismic Survey ◽  
Self Organizing Maps ◽  
Early Introduction ◽  
Statistical Measures ◽  
Seismic Waveform ◽  
Occurrence Matrix ◽  
Single Trace

In recent years, 3D volumetric attributes have gained wide acceptance by seismic interpreters. The early introduction of the single-trace complex trace attribute was quickly followed by seismic sequence attribute mapping workflows. Three-dimensional geometric attributes such as coherence and curvature are also widely used. Most of these attributes correspond to very simple, easy-to-understand measures of a waveform or surface morphology. However, not all geologic features can be so easily quantified. For this reason, simple statistical measures of the seismic waveform such as rms amplitude and texture analysis techniques prove to be quite valuable in delineating more chaotic stratigraphy. In this paper, we coupled structure-oriented texture analysis based on the gray-level co-occurrence matrix with self-organizing maps clustering technology and applied it to classify seismic textures. By this way, we expect that our workflow should be more sensitive to lateral changes, rather than vertical changes, in reflectivity. We applied the methodology to a remote sensing image and to a 3D seismic survey acquired over Osage County, Oklahoma, USA. Our results indicate that our method can be used to delineate meandering channels as well as to characterize chert reservoirs.

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