Computational approaches for structural analysis of wood specimens
The structure tensor (ST), also named a second-moment matrix, is a popular tool in image processing. Usually, its purpose is to evaluate orientation and to conduct local structural analysis. We present an efficient algorithm for computing eigenvalues and linking eigenvectors of the ST derived from a...
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| Format: | Article |
| Language: | English |
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De Gruyter
2024-12-01
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| Series: | Reviews on Advanced Materials Science |
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| Online Access: | https://doi.org/10.1515/rams-2024-0073 |
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| _version_ | 1850088625454186496 |
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| author | Chakkour Tarik |
| author_facet | Chakkour Tarik |
| author_sort | Chakkour Tarik |
| collection | DOAJ |
| description | The structure tensor (ST), also named a second-moment matrix, is a popular tool in image processing. Usually, its purpose is to evaluate orientation and to conduct local structural analysis. We present an efficient algorithm for computing eigenvalues and linking eigenvectors of the ST derived from a material structure. The performance and efficiency of our approach are demonstrated through several numerical simulations. The proposed approach is evaluated qualitatively and quantitatively using different two-dimensional/three-dimensional wood image types. This article reviews the properties of the first- and second-order STs, their properties, and their application to illustrate their usefulness in analyzing the wood data. Our results demonstrate that the suggested approach achieves a high-quality orientation trajectory from high-resolution micro-computed tomography (μ{\rm{\mu }}CT)-imaging. These orientations lead to establishing a description of fiber orientation states in thermo-mechanical models for fiber-reinforced composite materials. We conclude with an overview of open research and problem directions. |
| format | Article |
| id | doaj-art-8a77cef233234cdea0c3e71714795446 |
| institution | DOAJ |
| issn | 1605-8127 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Reviews on Advanced Materials Science |
| spelling | doaj-art-8a77cef233234cdea0c3e717147954462025-08-20T02:42:59ZengDe GruyterReviews on Advanced Materials Science1605-81272024-12-01631pp. 497410.1515/rams-2024-0073Computational approaches for structural analysis of wood specimensChakkour Tarik0LGPM, CentraleSupélec, Université Paris-Saclay, Centre Européen de Biotechnologie et de Bioéconomie (CEBB), 3 Rue des Rouges-Terres, 51110 Pomacle, FranceThe structure tensor (ST), also named a second-moment matrix, is a popular tool in image processing. Usually, its purpose is to evaluate orientation and to conduct local structural analysis. We present an efficient algorithm for computing eigenvalues and linking eigenvectors of the ST derived from a material structure. The performance and efficiency of our approach are demonstrated through several numerical simulations. The proposed approach is evaluated qualitatively and quantitatively using different two-dimensional/three-dimensional wood image types. This article reviews the properties of the first- and second-order STs, their properties, and their application to illustrate their usefulness in analyzing the wood data. Our results demonstrate that the suggested approach achieves a high-quality orientation trajectory from high-resolution micro-computed tomography (μ{\rm{\mu }}CT)-imaging. These orientations lead to establishing a description of fiber orientation states in thermo-mechanical models for fiber-reinforced composite materials. We conclude with an overview of open research and problem directions.https://doi.org/10.1515/rams-2024-0073structure tensor3d reconstructionimage processingtomographyanisotropymechanical modeling |
| spellingShingle | Chakkour Tarik Computational approaches for structural analysis of wood specimens Reviews on Advanced Materials Science structure tensor 3d reconstruction image processing tomography anisotropy mechanical modeling |
| title | Computational approaches for structural analysis of wood specimens |
| title_full | Computational approaches for structural analysis of wood specimens |
| title_fullStr | Computational approaches for structural analysis of wood specimens |
| title_full_unstemmed | Computational approaches for structural analysis of wood specimens |
| title_short | Computational approaches for structural analysis of wood specimens |
| title_sort | computational approaches for structural analysis of wood specimens |
| topic | structure tensor 3d reconstruction image processing tomography anisotropy mechanical modeling |
| url | https://doi.org/10.1515/rams-2024-0073 |
| work_keys_str_mv | AT chakkourtarik computationalapproachesforstructuralanalysisofwoodspecimens |