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OCR for page 51
APPENDIX A
Proposed Test Methods
Disclaimer
"The proposed test methods are recommendations of the NCHRP Project 4-30A staff at Texas
Transportation Institute. These methods have not been approved by NCHRP or by any AASHTO
Committee or formally accepted for the AASHTO specifications."
A-1
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A-2 Test Methods for Characterizing Aggregate Shape, Texture, and Angularity
Proposed Standard Method of Test for
Shape, Angularity, and Texture of Aggregate Particles
Using the Aggregate Imaging System (AIMS)
1. Scope
1.1 This method quantifies three-dimensional shape, angularity, and texture of coarse
aggregate particles as well as angularity of fine aggregate particles. Testing and analyses
are accomplished using the integrated Aggregate Imaging System (AIMS).
1.2 Analysis of Coarse Aggregates (Method A)--This method uses aggregates that are
retained on a 4.75-mm (No. 4) sieve.
1.3 Analysis of Fine Aggregates (Method B)--This method uses aggregates that pass
through a 4.75-mm (No. 4) sieve.
1.4 Aggregates scanned using this process should be washed to remove clay, dust, and other
foreign materials and separated into the appropriate sizes before being analyzed.
1.5 This standard does not purport to address all of the safety problems, if any, associated
with its use. It is the responsibility of the user of this standard to establish appropriate
safety and health practices and determine the applicability of regulatory limitations
prior to use.
2. Referenced Documents
2.1 ASTM Standards:
D 75 Practice for Sampling Aggregates
C 136 Test Method for Sieve Analysis of Fine and Coarse Aggregates
C 702 Practice for Reducing Samples of Aggregate to Testing Size
E 11 Specification for Wire-Cloth Sieves for Testing Purposes
3. Terminology
3.1 Definitions:
3.1.1 Shape--describes the overall 3-dimensional shape of aggregate particles, e.g.,
round, elliptical, flat. The AIMS software sorts the three dimensions based on
length and calculates the sphericity index as shown in Equation (1):
d s .d I
Sphericity = 3
2
( A-1)
dL
where dL is the longest dimension, dI is the intermediate dimension, and ds is the
shortest dimension. A sphericity value of one indicates that a particle has equal
dimensions.
3.1.2 Angularity--is related to the sharpness of the corners of 2-dimensional images of
aggregate particles. The angularity is analyzed using the gradient method. This
method quantifies the change in the gradient on a particle boundary. The gradi-
ent method starts by calculating the inclination of gradient vectors on particle
boundary points from the x-axis (horizontal axis in an image). The average
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Proposed Test Methods A-3
change in the inclination of the gradient vectors is taken as an indication of angu-
larity as follows:
N -3
1
Angularity (Gradient Method) = i - i + 3 ( A-2)
N i =1
-1
3
where the subscript i denotes the ith point on the boundary of a particle, and N
is the total number of points on the boundary.
3.1.3 Texture--describes the relative smoothness or roughness of aggregate particles
surfaces. The wavelet method is used to quantify texture. The wavelet analysis
gives the texture details in the horizontal, vertical, and diagonal directions in three
separate images. The texture index is taken at a given decomposition level as the
arithmetic mean of the squared values of the wavelet coefficients for all three
directions. The texture index is expressed mathematically as follows:
1 3 N
( Di , j ( x , y )) ( A-3)
2
Texture Indexn =
3N i =1 j =1
where n denotes the level of decomposition and i takes a value 1, 2 or 3, for the
three directions of texture, and j is the wavelet coefficient index.
4. Summary of Methods
4.1. Method A--Analysis of coarse aggregates includes 3-dimensional shape, angularity, and
texture. The analysis starts by placing 56 aggregates particles on the aggregate tray at the
specified locations. A 0.25X objective lens and camera acquire images of coarse aggre-
gate particles. The maximum field of view achieved in the coarse aggregate module is
52.8 × 70.4 mm. The camera and video microscope assembly move incrementally in the
x direction at a specified interval, acquiring an image of one particle at each increment.
Once the x-axis range is complete, the aggregate tray moves in the y-direction for a spec-
ified distance, and the x-axis motion and image acquisition process is repeated. This
process continues until all 56 aggregates are scanned. Two separate scans are conducted
using backlighting and top lighting, respectively. Backlighting is used to acquire two-
dimensional images for the analysis of angularity, while top lighting is used for acquir-
ing images for surface texture analysis. These two types of scans are necessary for
complete analysis of coarse aggregates shape.
4.2. Method B--Analysis of fine aggregate angularity. The 0.5X objective lens is used for
acquiring images. The analysis starts by uniformly spreading a few grams of fine aggre-
gate particles on the aggregate tray. Backlighting is used to acquire all images in this
analysis. The camera and video microscope assembly move automatically over the
aggregate tray until the entire area is scanned. In each x-y scan, the z-location of the
camera is stipulated to meet specified resolution criteria. Aggregates that are not within
the size range for which the scan is conducted are removed from the image.
5. Significance and Use
5.1. Shape, angularity, and surface texture of aggregates have been shown to directly affect
the engineering properties of highway construction materials such as hot mix asphalt
concrete, Portland cement concrete, and unbound aggregate layers. Most methods
currently in use for measuring these properties of aggregate particles are indirect
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A-4 Test Methods for Characterizing Aggregate Shape, Texture, and Angularity
measurements of the desired properties. This test method provides direct measurement
of aggregate shape, angularity, and texture and thus provides consistent values that are
comparatively more beneficial for use in software designed to predict performance of
highway pavements and structures.
6. Apparatus
6.1. The AIMS is an integrated system composed of a camera, video microscope, aggregate
tray, backlighting and top-lighting systems, and associated software.
7. Sampling
7.1. Obtain aggregate specimens in accordance with Practice D 75, and reduce the specimen
to an adequate sample size in accordance with Practice C 702.
8. Preparation of Test Samples
8.1. Wash and oven dry the reduced sample at 110 ± 5°C (230 ± 9°F) to substantially con-
stant mass. The coarse aggregate sample should contain at least 56 particles. The fine
aggregate sample should be about 50 gm.
9. Procedure
9.1. Analysis of Coarse Aggregate Angularity, Texture, and Shape
9.1.1. The user must ensure that the objective lens used is 0.25X and that the micro-
scope is placed in the coarse position on the dovetail slide. The objective lens
can be replaced by removing the fiber-optic ring light by unscrewing the three
screws on the ring. Then unscrew the ring light holder from the lower end of
the microscope. The user will be required to install the lens (0.25X in this case),
return back the ring holder, and fix the top lighting ring back.
9.1.2. Position the microscope on the dovetail slide by releasing the knob of the
retaining pin on the left side and sliding the microscope assembly upward or
downward until the "coarse" labels on the left-hand side of the two pieces line
up. The user needs to ensure that the retaining pin is engaged to secure the
microscope. Then tighten the thumbscrew on the right-hand side of the micro-
scope assembly.
9.1.3. On the integrated computer desktop, double click on the "AIMS" icon. The pro-
gram interface will display a window along with a real time image (Figure A-1-1).
On the program interface window, there are several active buttons with labels
that indicate the process they perform.
9.1.4. Start the analysis by clicking on the "Project Settings" button. The user must
select a name for the project so the analysis results for the aggregate sample will
be saved in a file name under the specified directory. This step will allow the user
to specify type and size of aggregates to be analyzed. The user is required to click
on the "Modify Parameters" button that is available in the "Analysis Parame-
ters" window (Figure A-1-2).
9.1.5. At the "Project Parameters" window (Figure A-1-3), enter the drive and direc-
tory path desired for the project. Then enter a project name for the aggregates
to be analyzed. Then from the "Aggregate Range" drop-list, the user can select
the type of aggregate to be evaluated. For Method A, the user must select
"Coarse." Then click "OK."
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Proposed Test Methods A-5
Figure A-1-1. Computer screen for setting up an AIMS test.
Figure A-1-2. "Analysis Parameters" window for AIMS test setup.
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A-6 Test Methods for Characterizing Aggregate Shape, Texture, and Angularity
Figure A-1-3. "Project Parameters" window for AIMS test setup.
9.1.6. Clicking the "OK" button on the "Project Parameters" window will display the
"Coarse Aggregate Parameters" window (Figure A-1-4). From the "Analysis
Type" drop-list, the user must select the type of analysis to be performed (i.e.,
Angularity, in this case), and click the "OK" button. A "Coarse Aggregate Pa-
rameters" window will appear, and the user must select from the drop-list the
aggregate size to be analyzed (Figure A-1-5) and click the "OK" button. The first
program interface window will appear, showing the information previously
entered for current project settings.
9.1.7. Turn on the light beneath the aggregate tray, and allow it to warm up for a min-
imum of two minutes.
9.1.8. To calibrate the camera and microscope, click on the "Camera Setup" button.
An "AIMS Camera Setup" window will appear, showing a real-time image
(Figure A-1-6). Now, the user must focus the camera and microscope on the
calibration point marked on the aggregate tray. This point will be used as a ref-
erence point for the scan where (x, y, z) coordinates are set to (0, 0, and 0). The
user must ensure that the target point is in the center of the image by moving
the aggregate tray in x and y direction using the joystick on the controller box.
This process is easier if the magnification is at the lowest level (M = 1.0). A mag-
nification of 1.0 is achieved by rotating the dial on top of the controller box
while the switch button on the front of the controller is at zoom position. The
magnification (M-value) appears on the digital screen on the controller box;
this value will change when rotating the dial. The minimum value is 1.0 and the
maximum value is 16, where maximum magnification is achieved.
9.1.9. After centering the calibration point in the image window, the user must click
on the "16X" button. Clicking this button will cause the microscope to zoom in
and achieve maximum magnification. If the point is not clear or not viewable
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Proposed Test Methods A-7
Figure A-1-4. "Coarse Aggregate Parameters" window for
AIMS test setup.
Figure A-1-5. "Coarse Aggregate Parameters" window for
AIMS test setup.
OCR for page 58
A-8 Test Methods for Characterizing Aggregate Shape, Texture, and Angularity
Figure A-1-6. "AIMS Camera Setup" window.
in the image, move the switch at the front of the controller box to the "Focus"
position. Then rotate the dial on top of the controller box to move the micro-
scope up or down until the image becomes clear. If the calibration point does
not appear in the image window, move the joystick in x and/or y direction until
the calibration point appears in the center of the image (Figure A-1-8).
Put the switch in the focus position, and use the dial to focus the image at
the maximum magnification (M = 16). This approach is illustrated in Figures
A-1-6, A-1-7, and A-1-8.
9.1.10. Once the calibration point is centered and well focused in the image, tap the
"@" on the controller. This button will cause the microscope to perform auto-
focusing and achieve the best image. Then, tap the "Zero" button on the con-
troller box. Then tap "Home." The "Zero" button will set the x, y, and z
coordinates to 0, 0, and 0, respectively. The "Home" button will cause the cam-
era and microscope to return to the start point after finishing the scan. Then,
click the "Done" button on the "AIMS Camera Setup" window; this window will
close, and the program interface window will appear again.
9.1.11. Image acquisition begins by clicking on the "Acquire Images" button on the com-
puter screen. A new message window will appear giving the option for per-
forming camera setup. If camera setup was not performed in the previous step,
it can be done here; otherwise, select "No," if already performed (Figure A-1-9).
When omitting the camera setup option, a new message window appears with
instructions (Figure A-1-10).
9.1.12. The term "camera origin,"on the screen, signifies camera setup may be performed
at this time; however, that is normally performed in the previous step. If so, click
cancel, and place aggregate particles on the tray at the indicated locations. Place-
ment of aggregates can be performed at the beginning, but in that case, the user
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Proposed Test Methods A-9
Figure A-1-7. Calibration point centered at an intermediate magnification.
Figure A-1-8. Calibration point centered, focused, and at maximum magnification.
OCR for page 60
A-10 Test Methods for Characterizing Aggregate Shape, Texture, and Angularity
Figure A-1-9. Window providing second opportunity for
camera setup.
Figure A-1-10. Window providing options for AIMS test setup.
must ensure that the calibration mark is exposed so the camera setup can be
performed. If calibration has been performed, one can place aggregates on every
marking including the calibration mark. Placement of the aggregates begins by
placing a translucent sheet (Mylar film) between the aggregate tray and the light-
ing table, which has an alignment grid indicating the position for 56 particles
OCR for page 61
Proposed Test Methods A-11
(Figure A-1-11). The Mylar sheet is prepared such that the spacing between the
center of the particles is approximately 50 mm in the x-direction and 40 mm in
the y-direction. To ensure that the aggregates are properly aligned, the two mark-
ings on the right side of the glass aggregate tray should align with the corre-
sponding markings on the Mylar grid sheet (Figure A-1-12). Remove grid sheet
after all the particles are positioned. Figure A-1-13 shows the coarse aggregates
properly positioned on the glass tray.
9.1.13. After all instructions have been followed, click "OK," and AIMS will start scan-
ning. Upon scanning all aggregate particles on the aggregate tray, the camera
will return to the starting point. Figure A-1-14 shows an example of an image
from the scanning process.
Figure A-1-11. Aggregate tray with Mylar grid sheet
showing proper positions of aggregate particles.
Figure A-1-12. Close-up view of Mylar sheet over light
table. (Note: objects in photo appear misaligned due to
parallax error. Look straight down on light table to
achieve the optimum alignment.)
OCR for page 73
Proposed Test Methods A-23
MultipleRatio Analysis
Individual Size Fractions Grouped by F&E Ratios
100
North Carolina #57 A 3/8x4 1/2x3/8 3/4x1/2 1x3/4
90
% Maximum to Minimum 3:1 = 23.5% 5:1 = 4.1%
80
(granite)
70
60
50
40
30
20
10
0
1:1 2:1 3:1 4:1 5:1 >
Flat and Elongated Ratios
Figure A-2-1. View of the original prototype multiple
ratio analysis system.
Figure A-2-2. View of a commercially-available multiple
ratio analysis system.
OCR for page 74
A-24 Test Methods for Characterizing Aggregate Shape, Texture, and Angularity
9.2. The MRA system uses five different colors to represent five different flat and elongated
ratios (5:1). Therefore, prepare five empty bowls
with the same color indicators to receive the aggregates as they are categorized by the
MRA system. Place the bowls near the caliper.
9.3. Select a single aggregate particle from the sample and place it in the caliper with the
maximum dimension in the vertical orientation. Slowly lower caliper head until it con-
tacts the particle. Press the foot pedal to record the maximum dimension of the parti-
cle on the computer.
9.4. Place the same particle under the caliper with the minimum dimension in the vertical
orientation. Slowly lower caliper head until it contacts the particle. Press the foot pedal
to prompt the computer to record the minimum dimension of the particle and calcu-
late the flat and elongated ratio category of the aggregate particle.
9.5. When the color code appears on the screen, place the aggregate particle in the appro-
priate color-coded bowl.
9.6. Select another aggregate particle and repeat Steps 9.3 through 9.5. Repeat these steps
with all aggregate particles in the sample.
9.7. Weigh and determine the mass of the aggregate particles in each bowl. Sum the masses
of the aggregate particles in all five bowls. Determine the percentage of aggregate par-
ticles in each flat and elongated category by dividing the mass of particles in each bowl
by the total mass of all particles.
9.8. Alternatively, count the number of aggregate particles in each bowl. Sum the number
of aggregate particles in all five bowls. Determine the percentage of aggregate particles
in each flat and elongated category by dividing the number of particles in each bowl by
the total count of all particles.
OCR for page 75
Proposed Test Methods A-25
Proposed Standard Test Method for
Volume, Flat and Elongated Ratio, Angularity, and
Surface Texture of Coarse Aggregate Particles
Using the University of Illinois Aggregate Image
Analyzer (UIAIA)
1. Scope
1.1. This method is intended for simple three-dimensional (3-D) reconstruction of indi-
vidual coarse aggregate particles for volume, flat and elongated ratio, angularity, and
surface texture of coarse aggregate particles. Testing and analyses are performed using
the integrated University of Illinois Aggregate Image Analyzer (UIAIA).
1.2. Analysis of Coarse Aggregates--This method uses aggregates that are retained on a
4.75-mm (No. 4) sieve.
1.3. Coarse aggregates scanned using this process should be washed to remove clay, dust,
and other foreign and deleterious materials and separated into the appropriate sizes
before being analyzed.
1.4. This standard does not purport to address all of the safety problems, if any, associated with
its use. It is the responsibility of the user of this standard to establish appropriate safety and
health practices and determine the applicability of regulatory limitations prior to use.
2. Referenced Documents
2.1. ASTM Standards:
D 75 Practice for Sampling Aggregates
C 136 Test Method for Sieve Analysis of Fine and Coarse Aggregates
C 702 Practice for Reducing Samples of Aggregate to Testing Size
E 11 Specification for Wire-Cloth Sieves for Testing Purposes
3. Terminology
3.1. Definitions:
3.1.1. Volume--with three orthogonally positioned digital cameras, the UIAIA aggre-
gate image analysis system has the ability to perform volume computation for
an aggregate particle. An estimate of its weight can then be determined using
the known bulk specific gravity. The imaging based volume computation is
achieved by combining the information in the three 2-D binary images as
shown in Figure A-3-1. The 3-D space is meshed into a 3-D array of pixel
cuboids or voxels. It is then simply required to count the number of voxels cor-
responding to the particle contained in the rectangular box in Figure A-3-1. Any
voxel belonging to the particle has the corresponding three projection pixels in
the x-y, y-z, and z-x planes. The number of voxels that satisfies this condition
finally gives the volume of the particle in units of pixel length cube. The volume
computation program used in the UIAIA scans over the entire 3-D space and
examines if each voxel belongs to the particle.
3.1.2. Flat and Elongated Ratio (F&E Ratio)--describes the overall 3-dimensional
shape of aggregate particles. The UIAIA software sorts the evaluated aggregate
particles into three categories: F&E Ratio <3:1, 3:1 < F&E Ratio < 5:1 and F&E
Ratio > 5:1, based on F&E Ratio calculated using Equation 1:
OCR for page 76
A-26 Test Methods for Characterizing Aggregate Shape, Texture, and Angularity
x
z y
Ymax
ax
Zm
Xmax
Figure A-3-1. The smallest rectangular box
encompassing a particle.
Longest Dimension
F&E Ratio = ( A-1-1)
Shortest Perpendicular Dimension
where Longest Dimension is the longest dimension measured by UIAIA software
from the three orthogonally positioned camera images, i.e., the top, side and
front images. Shortest Perpendicular Dimension is the shortest dimension from
the three images, which is perpendicular to the Longest Dimension as shown in
Figure A-3-2.
3.1.3. Angularity Index (AI)--is related to the corner sharpness of 2-D images of aggre-
gate particles. The angularity index (AI) is defined based on tracing the changes
in slope of the particle image outline obtained from each of the top, side and
front images. The outline of each image is extracted and approximated by an
n-sided (n is taken as 24 in the AI definition) polygon as shown in Figure A-3-3.
The frequency distribution of the changes in the vertex angles is established in
10-degree class intervals. The number of occurrences in a certain interval and
the magnitude are then related to the angularity of the particle profile. Accord-
ingly, the AI procedure first determines an angularity index value for each 2-D
image as shown in Equation A-1-2:
170
Angularity , A = e × P(e) ( A-1-2)
e =0
where e is the starting angle value for each 10-degree class interval and P(e) is
the probability of each angle change in the range e to (e+10).
Then, a final AI is established for the particle according to Equation A-1-3, by
taking a weighted average of its angularity determined for all three views. The
AI has the same degree unit as an angle does.
3
( Angularityi × Areai )
AI = i =1
3
( A-1-3)
Areai
i =1
shortest dimension,
perpendicular to the
longest dimension
longest dimension
Figure A-3-2. The longest
and shortest dimensions of
a coarse aggregate particle.
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Proposed Test Methods A-27
3 4
3
2
2
n=1 1
n = 24
n-1
Figure A-3-3. An n-sided polygon
approximating the outline of an
aggregate particle.
3.1.4. Surface Texture (ST)--describes the surface irregularities of aggregate particles.
The surface texture of an aggregate particle is defined using an image analysis
technique known as Erosion and Dilation. Erosion cycles followed by the same
number of dilation cycles tend to smooth the surface of a particle by losing shape
peaks and patching sharp dents on the boundary. The image area difference
before and after erosion and dilation of the same number of cycles leads to the
definition of the ST for one of the three particle projection images as shown in
Equation A-1-4:
A1 - A2
ST = × 100 ( A-1-4 )
A1
where
ST = Surface texture parameter for each 2-D image;
A1 = Area (in pixels) of the 2-D projection of the particle in the image;
A2 = Area (in pixels) of the particle after performing a sequence of "n" cycles of
erosion followed by "n" cycles of dilation.
Then, an ST index, denoted as STparticle, is established for the particle by taking a
weighted average of each ST determined from all three views, which measures
the overall surface irregularities of a particle. STparticle, is computed as according
to Equation (A-1-5). The ST is a dimensionless quantity, as it measures the ratio
of the areas before and after erosion and dilation.
3
(STi × Areai )
STparticle = i =1
3
( A-1-5)
Areai
i =1
where i takes values from 1 to 3 for top, front, and side orthogonal views. STi is
the surface texture parameter for each 2-D image, and Areai is the correspon-
ding area of each 2-D image.
4. Summary of Method
4.1. Analysis of coarse aggregate particles includes determining volume, flat and elongated
ratio, angularity, and surface texture. The UIAIA features a moving conveyor belt that
carries the individual aggregate particle into the view of a sensor, which detects the
particle and immediately triggers the cameras. Once triggered, the three synchronized
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A-28 Test Methods for Characterizing Aggregate Shape, Texture, and Angularity
cameras capture in one-tenth of a second the images of the front, top, and side views of
the particle. The captured images are then processed for size and shape properties and
indices using software developed specifically for this application.
5. Significance and Use
5.1. Volume, shape, angularity, and surface texture of coarse aggregates have been shown to
directly affect the engineering properties of highway construction materials such as hot
mix asphalt concrete, Portland cement concrete, and unbound aggregate layers. Most
methods currently in use for measuring these properties of aggregate particles are indi-
rect measurements of the desired properties. This test method provides objective and
direct measurements of aggregate volume, shape (flatness and elongation), angularity,
and texture to quantify these properties and provide repeatable results that are compar-
atively more beneficial for use in performance prediction of highway pavements and
structures.
6. Apparatus
6.1. The UIAIA is an integrated system with a fixture framework for mounting and posi-
tioning the cameras, sensor, and other components. Three progressive scan CCD cam-
eras are adopted to capture the images of moving particles, which are commonly used
in motion control applications. The mechanical details of the UIAIA include a working
conveyor belt operated using a variable speed AC motor, which provides smooth and
steady operation at speeds as low as 3 inches/sec. Three fluorescent lights were used
behind the cameras to provide adequate brightness. A black background was provided
for all three views in order to provide a contrast and collect sharp images.
7. Sampling
7.1. Obtain aggregate specimens in accordance with Practice D 75, and reduce the specimen
to an adequate sample size in accordance with Practice C 702.
8. Preparation of Test Samples
8.1. Wash and oven dry the reduced sample at 110 ± 5°C (230 ± 9°F) to substantially constant
mass, typically 1 or 2 kilograms of aggregates depending on the average particle sizes.
9. Procedure
9.1. UIAIA System Setup--the UIAIA system is shown in Figure A-3-4 with an operator.
Turn on the AC motor and warm up the system by keeping the AC motor running for
ten minutes, so that the conveyor can move smoothly and steadily. Turn on the cameras
and the sensor, and adjust the lens of the cameras until images of particles with sharp
boundaries are obtained. Before image acquisition starts, take the images of a dummy
calibration specimen to make sure the cameras and sensors work properly.
9.2. UIAIA System Calibration--calibration is a process by which measurements made in
pixels from digitized images can be converted to equivalent engineering units through
proportionality or equivalency factors. The calibration factors are determined from
images of standard objects with known dimensions. Such calibration factors are of the
form "X pixels = Y length units". Once the calibration procedure is completed and
calibration factors are established, the original configuration of the test setup including
the camera focus, image resolution, light conditions, and so on, should not be altered.
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Proposed Test Methods A-29
Figure A-3-4. Photo of the UIAIA system with operator
passing aggregate particles.
Commercially manufactured white colored, precision spheres of diameter 0.5-inch,
0.625-inch, 0.75-inch, and 1-inch were used as standard specimens to establish calibra-
tion factors in the UIAIA system. The relative sizes of the spheres are shown in Figure
A-3-5. The sizes of the standard specimens chosen are representative of typical coarse
aggregate particle sizes encountered in paving applications. Furthermore, the choice of a
regular shaped object such as a sphere was made to expedite the calibration process by mak-
ing it easier to detect and correct measurement irregularities between the different views.
To establish calibration factors, images of the spheres need to be captured while the belt
is moving. The diameters of the spheres are measured in pixel units from each of the
three views. Calibration can then be accomplished by taking an average of the sphere
diameter (in pixels) measured from the front, top, and side images for each trial and for
each sphere size. The calibration factor for each size is obtained by comparing the diam-
eters of the spheres in real dimensions in the form of "X pixels = Y length units". To
acquire images for the calibration process, please refer to Step 9.2 in this protocol.
Image Acquisition--to start the image acquisition of the aggregate sample, first go to
the software package of UIAIA, click on the LABVIEW file titled "triggered_capture"
that has an extension of ".vi". A window is opened as shown in Figure A-3-6.
Operators can decide whether to display images, use trigger, or save gray scale and/or
binary images during the image acquisition. Also, operators can specify the starting
number of images and path of the saved images. The time delays for the three cameras
indicate the time interval between the triggering of the sensor and the front camera, and
the time interval between the front camera and the top camera and the side one. These
three time delays have been calibrated, therefore should not be changed dramatically.
0.5"
0.625" 0.75"
1.0"
Figure A-3-5. Perfect spheres used for the
calibration of UIAIA system.
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A-30 Test Methods for Characterizing Aggregate Shape, Texture, and Angularity
Figure A-3-6. UIAIA user interface (virtual instrument [VI]) for image acquisition.
The image acquisition can be started for a washed and oven dried aggregate sample by
clicking on the arrow icon in the Tools bar of the user interface. An operator is needed
to drop the individual particles one by one onto the moving conveyor belt (see Figure
A-3-4). During the image acquisition process, captured images can be monitored by
both the audio signal and the acquired three images shown on the computer screen. All
images captured are automatically saved in a temporary folder in the computer.
9.3. Calculation of Coarse Aggregate Size and Shape Properties--the size and shape indices
from the three-camera based aggregate particle reconstruction, i.e., the volume, gradation,
flat and elongated ratio, angularity, and surface texture are computed using the algorithms
or the virtual instruments (VIs) processing the acquired images for each sample. Each
program to calculate each of these quantities is an individual VI file in UIAIA system.
9.3.1. Coarse Aggregate Volume
The imaging based volume computation is achieved by combining the informa-
tion in the three 2-D binary images as shown in Figure A-3-1. The 3-D space is
meshed into a 3-D array of pixel cuboids or voxels. It is then simply required to
count the number of voxels corresponding to the particle contained in the rectan-
gular box in Figure A-3-1. Any voxel belonging to the particle has the correspon-
ding three projection pixels in the x-y, y-z, and z-x planes. The number of voxels
that satisfies this condition finally gives the volume of the particle in units of pixel
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Proposed Test Methods A-31
length cube. The volume computation program used in the UIAIA scans over the
entire 3-D space and examines if each voxel belongs to the particle.
The volume computation algorithm can be viewed during operation as the three
front, top, and side images of an aggregate particle are switched one by one on
the screen. A screenshot of this process is shown in Figure A-3-7.
9.3.2. Coarse Aggregate F&E Ratio
Go to the software package of UIAIA, click on the LABVIEW file titled
"fe_sieve_maxinter" with the extension of .vi. The window as shown in Figure
A-3-8 will be opened. Set up the parameters as shown in Figure A-3-8 by enter-
ing the drive and directory path desired for the project, and specifying a proj-
ect name for the aggregates to be analyzed. The F&E Ratios are computed for
each particle in the aggregate sample by clicking on the arrow icon in the Tools
bar of the user interface. The F&E Ratios of all the particles are automatically
saved in an Excel file, feratio.xse in the Results folder under C:\, which needs to
be established beforehand. Three other Excel files will also be generated that
measure the sieve dimension, the maximum dimension and the minimum
dimension of the individual particles respectively. The sieve dimension will be
used to plot the gradation of the evaluated aggregate sample. The maximum
dimension and the minimum dimension report the length and width of the
individual particles.
9.3.3. Coarse Aggregate Angularity
Go to the software package of UIAIA, click on the LABVIEW file titled "angular-
ity" with the extension of .vi. A window as shown in Figure A-3-9 will be opened.
Set up the parameters as shown in Figure A-3-9 and the angularity index (AI) is
calculated for each particle in the aggregate sample by clicking on the arrow icon
Figure A-3-7. Screenshot showing operation of volume computation user
interface or VI.
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A-32 Test Methods for Characterizing Aggregate Shape, Texture, and Angularity
Figure A-3-8. Screenshot of user interface or VI for coarse aggregate F&E Ratio.
Figure A-3-9. Screenshot of user interface or VI for coarse aggregate angularity.
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Proposed Test Methods A-33
Figure A-3-10. Screenshot of user interface or VI for coarse aggregate surface texture.
in the Tools bar of the user interface. Angularity of all the particles will be auto-
matically saved in an Excel file, ang.xse in the Results folder under C:\.
9.3.4. Coarse Aggregate Surface Texture
Go to the software package of UIAIA, click on the LABVIEW file titled "surftex"
with the extension of .vi. The window as shown in Figure A-3-10 will be opened.
Set up the parameters as shown in Figure A-3-10; the surface texture (ST) index
is computed for each particle in the aggregate sample by clicking on the arrow
icon in the Tools bar of the user interface. Surface texture of all the particles will
be automatically saved in an Excel file, surftex.xls in the Results folder under C:\.
When the size and shape properties and indices, i.e., maximum, minimum, interme-
diate dimensions, gradation curve, flat and elongated ratio, angularity, and surface
texture, are calculated for all the individual aggregate particles in a sample, the aver-
age flat and elongated ratio, angularity, and surface texture can be calculated to eval-
uate the size and shape property of the aggregate sample.
10. UIAIA Analysis Workbook
10.1. The UIAIA Analysis Workbook contains additional software that can be used to plot the
gradation of the evaluated aggregate sample. The program is self-guided and easy to use.
