Estimating 3D fibre orientation in volume images

Axelsson, Maria

doi:10.1109/icpr.2008.4761631

Cited by 21 publications

(17 citation statements)

References 4 publications

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“…Our approach uses oriented filters to detect fibers, based on similar filters used by Shinohara et al [2010] to locate fibers in CT data. We chose this approach because of its demonstrated application to fiber detection in CT data, though alternatives [Axelsson 2008] are possible.…”

Section: Recovering the Orientation Fieldmentioning

confidence: 99%

Building volumetric appearance models of fabric using micro CT imaging

Zhao

Jakob

Marschner

et al. 2011

ACM SIGGRAPH 2011 Papers

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Figure 1: We build volumetric appearance models of complex materials like velvet using CT imaging: (left) CT data gives scalar density over a small volume; (center) we extract fiber orientation (shown in false color) and tile larger surfaces; and (right) we match appearance parameters to photographs to create a complete appearance model. Both fine detail and the characteristic highlights of velvet are reproduced. AbstractThe appearance of complex, thick materials like textiles is determined by their 3D structure, and they are incompletely described by surface reflection models alone. While volume scattering can produce highly realistic images of such materials, creating the required volume density models is difficult. Procedural approaches require significant programmer effort and intuition to design specialpurpose algorithms for each material. Further, the resulting models lack the visual complexity of real materials with their naturallyarising irregularities. This paper proposes a new approach to acquiring volume models, based on density data from X-ray computed tomography (CT) scans and appearance data from photographs under uncontrolled illumination. To model a material, a CT scan is made, resulting in a scalar density volume. This 3D data is processed to extract orientation information and remove noise. The resulting density and orientation fields are used in an appearance matching procedure to define scattering properties in the volume that, when rendered, produce images with texture statistics that match the photographs. As our results show, this approach can easily produce volume appearance models with extreme detail, and at larger scales the distinctive textures and highlights of a range of very different fabrics like satin and velvet emerge automatically-all based simply on having accurate mesoscale geometry.

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Section: Recovering the Orientation Fieldmentioning

confidence: 99%

Building volumetric appearance models of fabric using micro CT imaging

Zhao

Jakob

Marschner

et al. 2011

ACM SIGGRAPH 2011 Papers

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“…Other authors have considered materials consisting of naturally occurring–based fibres such as paper and wood‐based composite material as shown by Axelsson (); Axelsson & Svensson (). The authors used a structure tensor of derivatives, similar to the Hessian, except the Hessian consists of second derivatives.…”

Section: Introductionmentioning

confidence: 99%

Automatic diameter and orientation distribution determination of fibrous materials in micro X‐ray CT imaging data

Chiverton

Kao

Roldo

et al. 2018

Journal of Microscopy

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Fibrous nanomaterials such as electrospun materials have many uses ranging from tissue engineering to biosensors. High-resolution imaging is an important component in the characterization of these materials. Important parameters required to predict and study the properties of fibre rich materials include diameter and orientation distribution as well as fibre spacing. The orientations and the relative dimensions of the fibres can be measured via specially designed imaging software. Difficulties in this measurement process can arise if fibres are distributed in close proximity to each other in relation to the resolution of the imaging modality. For example, if some automation is required in the measurement process and, particularly, if the automated processes are not designed for situations where the fibres are in close proximity to each other. This work is therefore concerned with the development of automated measurement techniques to provide estimates of the diameters of fibres and also the orientation distribution. The software automatically detects special points in the fibrous materials where fibres can be considered to have some delineation from surrounding fibres. These sparse points are considered to be points at which estimates of the fibres' properties can be quantified. Aligned and randomly distributed electrospun poly(caprolactone) nanofibres were prepared. Imaging of these materials was performed with an X-ray Computer Tomography system with an image voxel size of 0.15 × 0.15 × 0.15 μm . Scanning Electron Microscopy images were also obtained. Fibre diameters estimated using images from both modalities using the developed techniques were found to be in agreement. Orientation distribution was summarized with multiscale entropy and found to be consistent with visual observation across different scales. LAY DESCRIPTION: Fibres are present in many types of materials which can include, for some materials, very small fibres e.g. a few nanometres in diameter. Very small fibres are present in collagen and elastin which are common tissues of many organs in many types of living things. The sizes of these very small fibres and how they are arranged are important information that can help in the understanding of the overall properties of these materials. Materials with very small fibres can also be synthesized using specialised techniques. The properties of these synthesized fibrous materials are also important to help in understanding how the materials will perform in various different applications. Applications are many and can range from tissue engineering to drug delivery. Some properties of these materials can be shown, visually, with the aid of 3D imaging techniques such as X-ray Computer Tomography (XCT) or in 2D, with Scanning Electron Microscopy (SEM) but at a higher magnification. The work described here is centred around the development of computer algorithms to automatically determine material properties from 3D XCT images. Tests are performed with material samples, where the fibres are aligned (in semi...

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“…In contrast, morphological approaches such as [7,8], or filter-based methods [10] would also be applicable in our case. Yet, algorithms using partial gray value derivatives [11,12] are more closely related to our method, and we expect these could produce similar results to those presented here.…”

Section: Introductionmentioning

confidence: 99%

Characterization of multilayer structures in fiber reinforced polymer employing synchrotron and laboratory X-ray CT

Wirjadi

Godehardt

Schladitz

et al. 2014

International Journal of Materials Research

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Specimens of carbon or glass fiber reinforced polymer can be imaged using both conventional laboratory X-ray micro-computed tomography equipment and synchrotron light sources. The image quality when using intense (partially) coherent synchrotron light is still superior, especially when applying phase-retrieval algorithms. In the resulting volume images, the fiber direction distribution and other mechanically relevant parameters such as volume fractions or layer thickness can be determined. In this contribution, we will demonstrate how fiber direction results can be used to detect regions with locally different fiber orientations in carbon or glass fiber reinforced polymer which arise in the molding process of such samples. To this end, we evaluate the three-dimensional fiber orientation tensor locally across the thickness of different specimens. For each resulting individual layer, we can automatically detect the layer thickness and the preferred fiber direction. These methods have been successfully applied to various commercial specimens. We will demonstrate results on volume images of samples from both synchrotron and laboratory micro-computed tomography and discuss the specific advantages and disadvantages in this application.

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Estimating 3D fibre orientation in volume images

Cited by 21 publications

References 4 publications

Building volumetric appearance models of fabric using micro CT imaging

Building volumetric appearance models of fabric using micro CT imaging

Automatic diameter and orientation distribution determination of fibrous materials in micro X‐ray CT imaging data

Characterization of multilayer structures in fiber reinforced polymer employing synchrotron and laboratory X-ray CT

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