Three-dimensional Image Analysis Software
Image processing of glass fiber reinforced plastics
Case Example
Presentations at the 18th Annual Meeting of the Japan Societyof Polymer Processing (July, 2007), and the 6th Symposium on
Non-destructive Evaluation using Ionizing Radiation
Title: 3D image analysis by X-ray CT for glass fiber within resin castWhen casting resin added with glass fiber, the orientation of theThree-dimensional analysis of fiber structure

fiber have strong connection with its mechanical properties andABC

casting defects such as warpage. We used an industrial X-ray CTdevice as a convenient method to observe fiber orientation in acast plate. The shapes and distribution of the fibers were examined based on three-dimensional images. We used ExFact Analysis to analyze the fiber orientations in the skin and core layers,
whose results were then compared to the ones obtained throughcomputer simulations.

The above figure shows the same region of a volume data in four different representation, layered from the back to the front, in the order ofprocessing procedure.
The first layer in gray scale is the original CT image displayed semi-transparently, and the second layer is the same image with Medial Axis overlaid
on it. The fourth layer shows the vectors that indicate local trends in fiber

Skin Layer
Core Layer
Skin Layer
thickness direction
perpendicular direction
flow direction

orientation, and the third layer is the same image with Medial Axis overlaid
on it.
The vectors were obtained by dividing the volume data into 4 x 4 x 2
cuboids and calculating the average moment of inertia of all Medial Axesfor respective regions. Colors in the rainbow spectrum shows the quantity

Sample3(plate thickness 3.0mm,gate thickness 1.5mm)

skin layer
core layer
skin layerof fibers detected. The quantity becomes larger toward the blue end andsmaller toward the red end.

Application Fields
Material engineering in generalincluding petroleum, rubber, plastics, resin, polymer, granules(dosage form), methane hydrate, concrete/gravel, fuel cell, carbon
nanotube, paper, pulp fiber, ceramic, catalyst, bone, dental/medical
material, precision/electronic component, semiconductor.

Input data format

ExFact® Analysis Product Lineup/ Specification Details
Product Lineup・ ExFact® Analysis for Porous/Particles
・ ExFact® Analysis for Fiber

Please use either or both, depending on the types of object materials.

Required Software

・ Exfact® VR Windows（64-bit version）		

* for preprocessing and rendering/display of image data.

Software Licensing

A series of tomographic image obtained through imaging devices
such as X-ray CT, CLSM and TEM tomography

・ USB Software Protection Device

Before conducting 3D image analysis on ExFact Analysis, the image

・ Operating System : All editions of Microsoft Windows 7/8,
Japanese/English versions supported.
・ At least 4GB of RAM
・ 1280 x 1024, full color screen resolution or higher
・ A USB port (for USB Software Protection Device)

stack needs to be preprocessed, including the extraction of theregion of interest, on ExFact VR. ExFact VR supports various fileformats including tiff, bmp, dicom and original forms of different
devices.

MA (Medial Axes)

System Requirements

11um ← fiber width → 55um

ExFact Analysis Series

Visualize your imagination

Specification and release time may change without notice.Company and product name are registration of trademark.
Imaging technologies such as X-ray CT, CLSM and TEM tomography provide a seriesof tomographic image of industrial products and materials for the construction of their
3D images. ExFact® Analysis, a software based on the novel concept of "Medial Axis"
to capture the complex structure of various objects, offers a tool to conduct statisticalevaluation/analysis on the properties of those 3D images, including shapes/distributionsof grains/voids, as well as orientations of fibers.

Three-dimensional Image Analysis Software

Basic Concepts

Graphs Plotted Based on Analysis Results
Newly Developed Segmentation Process
A cross sectional (tomographic) image obtained with imaging devices, such as X-ray CT,

新開発の二値化処理

basically consists of pixels of various gray values. Each of these pixels represents theExFact Analysis calculates various statistical values for material evaluation.

corresponding
point of imaged
object, with their gray values corresponding to試料の断層像
the material
X線CT等の画像デバイスでは、一般に材料密度に応じた濃淡で画素が構成され、density of the points.
On a digital 空間分解能が有限であるため、image, whose spatial resolution
has a certain limitation,が描画されます。
デジタル画像では、形状辺縁部の輝度値が真値

the intensity values of marginal
regionbecomelower than their true values (which is calledよりも低く描画され(Partialvolumeeffect)、さらにノイズやアーチファクト等も影響した結果、

moment of inertia

Existing Method

Fiber orientation distribution

Distribution of number of bonds on individual fibers"partialvolume effect"). This effect, along with noises and artifacts, makes it difficult to
材料と空隙が明確に分離した理想的な画像を得ることは簡単ではありません。
obtainideal image 新開発の二値化アルゴリズムを搭載し、
in which material phase and pore space
are clearly separated.
ExFactanAnalysisは、複雑に入り組んだ材料/空隙部分

Equipped with a newly developped segmentation
algorithm, 画像データに対して高低2つExFact Analysis carries outの形態を三次元的に考慮して二値化処理を行います。
原理的には、

histogram,where thevoxels with gray values higher than the high threshold are classified
ExFact VRに渡して、その後の画像処理に使用することもできます。

probablity

void-spacestructure. The software sets
two thresholds領域抽出の結果は、(high and low) onファイルとしてa 3D image
輝度値を統計的に処理することによって、輪郭を推定します。
into material phase, while those with lower values than the low threshold into void space.

New Method

moment of inertia

number of occurrence

Original Image

binalization process
based on its three-dimentional scanning of highly-intricate
material/の閾値を与え、材料/空隙どちらへ分類すべきか不確定な画像に関しては、注目する画素近傍のBinarization

The three principal axes of inertia forfibers are calculated, normalized to unit
length and plotted on a sphere.

Those with in-between gray values are classified into either of the two categories after theBonds are defined as the points at
which a fiber contact other fibers.

software statistically processces the gray values of their neighbouring voxels, providing
more probable contour estimation. The resultant output file after the segmentation can beused on ExFact® VR for further image processing.

bonds per fiber

Medial axis
ExFact Analysis constructs the "Medial Axis" of the object - skelton of void space

Distribution of crossing angles between fibers

Shortest path distribution
Medial Axis which are connectedfrom “m“ to “n” interface

represented in a union of one dimentional curves. This lower dimentional representation ofthe object, while preserving important geometric properties, is easier to analyze than a 3D
3D properties of the original object.

b-2

probablity

number of occurrence

Medial axis

a-1

image. ExFact Analysis uses the medial axis as the basis for understanding the complicatedPreparations for quantitative analysis

b-3
b-4
density

A crossing angle is defined as thesmallest of the angles made by twocrossing fibers.
probability density

These points are defined as “clusters,” shown in blue in the figures on the right. The angles

crossing angle (degrees)

between paths at clusters are then calculated. Paths are connected so as to make thestraightest lines possible. These straight lines are extracted as individual fibers. The fibers
Fiber length Distribution
all (av 143)

shortest paths (av 1.62671)

density

Flow Steps

branch-branch (av 176)

probability

are then calculated for their properties including length, orientation and crossing angles.

face 3--> 4 (av 1.68913)

b-3 is the shortest path for medical axis of “b“, so a-1 and b-3 arecountedprobability

First, fibers are divided where they contact, intersect or diverge, into individual paths.

cumulativeAll :a-1 , b-2 , b-3 , b-4

Shortest paths :a-1 , b-3

tortuosity

Shortest paths represent the flow channels of liquid, air and electricity in materials
such as porous filter and polymer.
branch-leaf (av 125)leaf-leaf (av 158)

Cluster: a point that joints paths
LL (leaf-leaf): a path that has no cluster connection at either end
BB (branch-branch): a path that connects to a cluster at each end

fiber length (microns)

Objects of analysis
Fibrous materials such as fibers, fuel cells
and wires.

Loading image data, extracting the region ofinterest, and converting the file to a format
readable on ExFact Analysis.

Conducting binarization on a 3D volume data,
separating material phase and void space,and proceeding with analysis processprobablity

3D visualization of themedial axis processed by
ExFact Analysis

leaf-leaf (av 1.29)

fiber tortuosity

number of occurrences

branch-branch (av 1.33)

branch-leaf (av 1.21)

Observing the 2D slice
images processed by
ExFact Analysis

All channels (white) and the flow channels from left to right interfaces (red)Tortuosity
all (av 1.26)

Plotting graphs ofvarious indices forstatistical evaluation ofmaterials

BL (branch-leaf): a path that connects to a cluster only at one ends: straight line - a and b

f: fiber length - a and b
Tortuosity (T) =fs

Tortuosity of a fiber is defined as its
length divided by the distance between two ends.
The value of tortuosity becomes thelowest, 1, when the length is equal tothe distance. The value increases as
the fiber becomes more tortuous.
Tortuosity is calculated for different
types of fibers (all, LL, BB and BL).

Visualization of 3D fiber orientation
by voxel mesh.

Each colored vector is composed of all

the fibers in the corresponding regions,interpreting the fibers as vectors. Theircolor represent the number of fibers.
In this case, the volume data of

400 x 400 x 400 voxels is divided into
4 x 4 x 4 = 64 blocks of

100 x 100 x 100 voxels.

Voxel mesh images can be made semi-transparent and overlaid on the original

CT image for a single layered image output.