Good Practice Guide to the use of MAVIS II
Jones C D, Plassmann P, Stevens R F, Pointer M R, McCarthy M B
Medical Imaging Research Unit Technical Report TR-07-06
University of Glamorgan
Extracts from this report may be reproduced provided the source is
acknowledged and the extract is not taken out of context.
Issued: July 2006
Faculty of Advanced Technology, University of Glamorgan, Pontypridd, CF37 1DL, Wales, UK.
http://www.glam.ac.uk/socschool/research/medical_imaging/index.php
Good Practice Guide to the use of MAVIS II
July 2006
Good Practice Guide to the use of MAVIS II
Jones C D (1), Plassmann P (1), Stevens R F (2), Pointer M R (3), McCarthy M B (4)
1) School of Computing, University of Glamorgan, Pontypridd, Mid-Glamorgan, CF37 1DL
2) Enabling Metrology Division, National Physical Laboratory, Teddington, TW11 0LW
3) Quality of Life Division, National Physical Laboratory, Teddington, TW11 0LW
4) Engineering and Process Control Division, National Physical Laboratory, Teddington, TW11 0LW
ABSTRACT
This guide relates to a non-contact instrument for measuring the dimensions and recording the
colour of open wounds such as leg ulcers. The instrument is known by the acronym
MAVIS II, and was developed by Isotec Imaging Ltd and the University of Glamorgan.
MAVIS II records two images from slightly different viewpoints to generate a stereo pair and
special software is used to scan both images pixel by pixel to match them up and compute the
wound dimensions. Dimensional calibration artefacts to provide measurement traceability and
a method of characterising the digital camera to produce CIE colorimetry from an RGB image
file have been developed by the National Physical Laboratory. This guide gives a brief
technical background to the system and combined with the instructions from the instrument
handbook will enable the user to obtain consistent and accurate measurement results.
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Good Practice Guide to the use of MAVIS II
ACKNOWLEDGEMENTS
The Department for Trade and Industry (DTI) Measurement for Innovators (MFI) programme
is designed to promote innovation by linking industry with the world-class expertise and
facilities contained within the UK’s National Measurement Institutions.
The calibration artefacts and measurement traceability for the wound measurement system
(MAVIS II) reported here were developed by the National Physical Laboratory through a
Joint Industry Project “MavisCal”, funded by the DTI as part of the MFI programme.
The project partners included Isotec Imaging Ltd, the company developing the instrument and
software; the University of Glamorgan who provided specialist skills for developing the
instrument; the Royal National Hospital for Rheumatic Diseases (RNHRD) in Bath who
provided the pilot clinical trials and NPL who provided expertise and traceability to national
measurement standards.
More information about the Measurement for Innovators programme is available on the
website www.npl.co.uk/measurement_for_innovators.
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Good Practice Guide to the use of MAVIS II
TABLE OF CONTENTS
Acknowledgements ................................................................................................................. iii
1. INTRODUCTION................................................................................................................ 1
1.1 Background ............................................................................................................ 1
1.2 MAVIS II ................................................................................................................ 2
2. GUIDE TO USING THE INSTRUMENT ........................................................................ 4
2.1 Switching On .......................................................................................................... 4
2.2 Taking Images ........................................................................................................ 4
2.3 Downloading Images to PC from CF Memory Card ......................................... 5
2.4 Making measurements using the MAVIS Software ........................................... 5
2.4.1 Selecting the image to measure ............................................................. 5
2.4.2 Drawing around the wound perimeter ................................................ 6
2.4.3 Inspecting results ................................................................................... 6
2.4.4 Saving results.......................................................................................... 7
2.5 Database functions ................................................................................................ 7
2.5.1 Main Screen: “Measured Images” ....................................................... 7
2.5.2 Results window ....................................................................................... 8
2.5.3 Tools to correct saving mistakes ........................................................... 8
2.6 Software installation.............................................................................................. 9
2.6.1 System check........................................................................................... 9
2.6.2 Install/Uninstall ...................................................................................... 9
2.6.3 Setup ...................................................................................................... 10
2.7 Changing the Target Light Battery ................................................................... 10
2.8 Recharging the camera battery .......................................................................... 11
2.9 Calibration Check ............................................................................................... 11
3. DIGITAL CAMERA CALIBRATION - COLOUR CHARACTERISATION .......... 12
3.1 Practical procedure ............................................................................................. 12
3.2 Modelling data ..................................................................................................... 13
4. SUMMARY ........................................................................................................................ 17
5. REFERENCES ................................................................................................................... 17
APPENDIX A1 - DIMENSIONAL CALIBRATION AND MEASUREMENTS ............. 17
A1.1 Initial Calibration of MAVIS system .............................................................. 18
A1.2 Dimension traceability using calibration artefacts ........................................ 19
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Good Practice Guide to the use of MAVIS II
FIGURES
Figure 1. Mock leg with artificial wounds. ............................................................................... 1
Figure 2. MAVIS II camera system ............................................................................................ 2
Figure 3. Mavis camera, dimensional and colour calibration artefacts ...................................... 3
Figure 4. Schematic of the digital camera characterisation procedure. ................................... 12
*
E ab
Figure 5. A histogram of values of CIELAB colour difference,
, obtained using a
24-patch GretagMacbeth ColorChecker chart, using L*, a*, b* input data. Also shown is
the associated cumulative frequency distribution ..................................................................... 12
Figure 6. Predicted CIELAB coordinates calculated using a quadratic model and
plotted as a function of their corresponding measured values .................................................. 16
Figure 7. A stereo image of a printed grid taken with MAVIS II during calibration. ............. 18
Figure 8. Estimation of the polynomial function used to calculate the depth of a point to give
its left-right disparity. ................................................................................................................ 19
Figure 9. Dimensional calibration artefact. ............................................................................. 20
Figure 10. Non-contact coordinate measuring machine.......................................................... 20
Figure 11. A range of dimensional calibration artefacts. ......................................................... 21
TABLES
Table 1. Typical dimensions of artefacts produced for MAVIS II ........................................... 22
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Good Practice Guide to the use of MAVIS II
1. INTRODUCTION
1.1 Background
MavisCal was a Joint Industry Project funded through the DTI Measurement for Innovators
scheme. The project supported the development of a portable instrument, MAVIS II, for
quick non-contact measurements on open wounds such as leg ulcers shown on the mock leg
in figure 1. The project partners included Isotec Imaging Ltd, the company developing the
instrument and software, the University of Glamorgan who provided specialist skills for
developing the instrument, the Royal National Hospital for Rheumatic Diseases (RNHRD) in
Bath who provided the pilot clinical trials and NPL who provided expertise and traceability
to measurement standards. In this application instrument calibration and measurement
traceability are important factors.
The incidence of chronic wounds is increasing along with diabetes in our ageing population.
Leg ulcer wounds heal slowly and monitoring is essential in determining progress and
specifying suitable treatment. Doctors sometimes use a simple technique to measure wound
area and volume on a weekly basis to decide if the wound is healing. By placing a transparent
sheet on top of the wound, a physician traces the wound perimeter and counts the squares
inside the line. The volume is measured by filling the wound with saline from a syringe – the
amount dispensed is the wound volume.
Figure 1. Mock leg with artificial wounds
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Good Practice Guide to the use of MAVIS II
In addition to being painful, these invasive procedures may carry a risk of cross-infection.
MAVIS II (Measurement of Area and Volume Instrumentation System) developed by Isotec
Imaging Ltd, is a portable system that avoids these issues. The camera system shown in
figure 2, along with special software, measures area and volume and records colour, noninvasively. Colour is an important parameter in monitoring the progress of the wound.
1.2 MAVIS II
To produce an instrument that can be afforded by a range of clinics the cost is kept down by
employing commercially available cameras and optics. Because dimensional accuracy is
affected by optical distortion and colour reproduction may vary between cameras and with
time it is essential that the instruments are calibrated. The MavisCal project supported the
development of three-dimensional calibration artefacts with textured surfaces and
investigated the factors affecting accurate colour recording.
Figure 2. MAVIS II camera system
MAVIS II is based around a digital camera and records two images of a wound from slightly
different viewpoints to generate a stereo pair. Special software is used to scan both images
pixel by pixel to match them up and compute the wound dimensions. The dimensional
calibration artefacts developed during this project are metal plates with spherical shapes cut
into the flat surfaces. The shaped surfaces have a texture pattern printed on them to enable the
camera system to identify corresponding areas in the two images of the surface. The shape of
the concave surface has been measured with a high precision coordinate measuring machine
and the area and volume of the artefacts computed. The artefacts are then measured using
MAVIS II and the results compared.
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Good Practice Guide to the use of MAVIS II
To ensure the colour measurements are consistent, a test target of colour patches as shown in
figure 3 is used. A procedure was devised during this project to characterise the digital
camera and this is applied (1).
A pilot trial to test the usability of the MAVIS II system was conducted at the Royal National
Hospital for Rheumatic Diseases in Bath and clinicians with an interest in wound healing and
the care of chronic wounds were invited to take part. The mock leg shown in figure 1 was
prepared with wounds that could be measured using traditional techniques such as alginate
casts. A measurement protocol and questionnaires were designed for the event so as to get as
much information as possible. Participants were given an introductory talk explaining the
background to MAVIS II and then invited to use the camera system on the artificial leg.
Feedback on the use and usefulness of the instrument proved to be positive and was
incorporated in the measurement procedure.
Figure 3. Development version of Mavis, dimensional and colour calibration artefacts
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Good Practice Guide to the use of MAVIS II
2. GUIDE TO USING THE INSTRUMENT
This section reproduces instructions from the instrument guidebook.
2.1 Switching On
1.
2.
3.
4.
Slide lever into ‘ON’ position
Set Dial to position ‘M’
Switch Flash on
Check batteries:
 Camera charged?
 Orange Flash light on?
 Target Lights working?
2.2 Taking Images
1. Apply wound sticker.
2. Push down orange target light switch.
3. At about 80 cm distance from the wound both
target beams will merge.
4. Move merged beams to the wound centre.
5. Hold target light switch and press camera
shutter button.
6. Control Image in camera display:
 Wound centred?
 Wound completely visible?
 Brightness: flash worked?
Note: Images are only shown after shooting.
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Good Practice Guide to the use of MAVIS II
2.3 Downloading Images to PC from CF Memory Card
Images are stored on the
Compact Flash (CF) card
of the camera.
For measurement, the
images have to be
transferred to the PC or
Laptop.
1. Remove CF card from camera.
2. Insert into PC or Laptop (you may need
an adapter for your computer to do this).
3. Start the MAVIS software.
4. Click on the
button to
start transferring images.
2.4 Making Measurements using the MAVIS Software
2.4.1 : Selecting the image to measure
1. Select
image
2. Click the
‘Measure’
button
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Good Practice Guide to the use of MAVIS II
2.4.2: Drawing around the wound perimeter
Drag rectangle to move
the zoomed area
Remove last
point(s) set
Zoom in
Zoom out
Click on
perimeter to
set points
Back to
Main Menu
When contour
is closed click
‘Next’ to start
calculations.
Drag this corner to adjust window size
2.4.3: Inspecting results

ROTATE:
Hold the left
mouse button
down while
dragging the
mouse pointer over
the image.

ZOOM:
Hold the right
mouse button
down while
moving the mouse
pointer up or
down.
Click the
button to continue.
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Good Practice Guide to the use of MAVIS II
2.4.4: Saving results
A
NEW PATIENT
1. Enter the patient’s name.
2. Click on ‘Create’:
3. Enter the wound name.
4. Click on ‘Create’
5. Click on “Save results”
B
EXISTING PATIENT
1. Select patient
2. Select wound
3. Click on ‘Save results’
2.5 Database Functions
2.5.1: Main Screen: “Measured Images”
Select wound
Show:
Select patient




Table
Graph
Plot
Gallery
Delete selected wound or
patient data
View image in 3D
Measure again
Browse
through
wound
images
Delete image shown
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Good Practice Guide to the use of MAVIS II
2.5.2: Results window
Results can be
copied to clipboard
for pasting into
Word or Excel
2.5.3: Tools to correct saving mistakes
Correct wrong patient
or wound name.
Move images
accidentally stored
under the wrong
wound. Also moves
wounds accidentally
stored under the
wrong patient.
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Good Practice Guide to the use of MAVIS II
2.6 Software Installation
2.6.1: System Check
2. Hardware (minimum requirements):
Operating System:
Processor:
RAM:
Hard Disk Space:
Screen Resolution:
Windows 98 or later
1.5 MHz
500 MB
100 MB
1024 x 768
1. DirectX requirements
Run the DirectX diagnostics tool on your PC
(Start ->Run->type ‘dxdiag’) and check:
DirectX Version:
9
Graphics Processor: Nvidia or Intel 3D
(others may also work)
Graphics Memory: 64 MB or more
If you have an older version of DirectX installed
you can download version 9 from:
www.microsoft.com/windows/directx/downloads
/default.asp
2.6.2: Install / Uninstall
Installation:
1. Insert CD into CD ROM drive
2. (If installation does not start automatically
run ‘Setup.exe’ on the CD)
3. Follow the installation instructions.
Removing MAVIS:
Delete the MAVIS folder into which has been
created in your ‘Program Files’ folder
(including all the files that are in it).
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Good Practice Guide to the use of MAVIS II
2.6.3: Setup
1. Start the MAVIS software.
2. Click on the
button to open the
Setup window.
3. User preferences for
delineation point size,
password protection and
automatic detection of
consistency checker.
4. Define the path where
MAVIS can find the
camera’s CF memory
card (insert CF card into
PC and browse).
5. Set this camera
parameter so that the
system can alarm you if
you have accidentally
changed them.
2.7 Changing the Target Light Battery
1. Move right projector half
downwards to access the battery.
2. Using a small screw driver prise
battery out of holder.
3. Replace with same type battery
(3V Lithium, type CR 2032)
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Good Practice Guide to the use of MAVIS II
2.8 Recharging the Camera Battery
1. Move right projector
half downwards to
access battery.
2. Open camera battery
compartment.
3. Click orange lever to remove battery
4. Insert battery into charger
NOTE: Charging is
completed when the
red light has
stopped flashing.
2.9 Calibration Check
1. Take an image of an NPL calibration artefact
(see 2.2 and Appendix A1)
2. Download the image (see 2.3)
3. Measure the artefact (see 2.4). Note that the
artefact will be automatically recognised and
outlined.
4. If an error is reported indicating that the
images are misaligned, return the camera to
Isotec Imaging for recalibration. Otherwise
the results of the artefact measurement will
be available for inspection.
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Good Practice Guide to the use of MAVIS II
3. DIGITAL CAMERA CALIBRATION - COLOUR CHARACTERISATION
3.1 Practical procedure
As shown in figure 4, the characterisation of a digital camera starts with the selection of a
suitable test target where the CIE colorimetry for each patch is known, calculated using the
required CIE illuminant and CIE standard observer. For example, CIE Standard Illuminant
D65 and the CIE 2 Standard Observer are usually appropriate. If these colorimetric data are
not available, then measurements of the spectral reflectance of each patch in the selected
target are required and the necessary CIE tristimulus values, X m ,Ym , Z m , and CIELAB
colorimetric coordinates, L*m , a*m , bm* , calculated.
Digital camera
+
electronic flash
Image R, G, B
Gamma correct
Model
Target L*, a*, b*
Predicted L*, a*, b*
Colour difference, E*
Figure 4. Schematic of the digital camera characterisation procedure.
1.
An image of the test target is made using the digital camera with the electronic flash unit
mounted on the camera. The image should be stored using the minimum processing
possible. Thus, if a typical photographic digital camera is used, then the images stored
should not be compressed.
2.
An image is also made of a sheet of neutral paper on which a grid has been drawn to
provide the exact location of the coloured patches in the chart. This grid will be used to
assess the uniformity of the illumination.
The R, G, B values for each of the pixels in the two images then need to be obtained. To
3.
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Good Practice Guide to the use of MAVIS II
do this, software is required that can open the image and calculate average R, G, B values
of an array of pixels (an ROI, Region of Interest): the number of pixels will be a function
of the size of the image but at least 200 should be used. This gives the average R, G, B
values of each patch in the colour target. This software is not supplied with the
instrument.
4.
A correction to account for the non-uniformity of the illumination is calculated using the
G pixel values of the image of the neutral paper. A factor, Fi, is calculated as:
Fi  MAX ( G ) / Gi
Where MAX(G) is the maximum G value of the pixels considered, and Gi is the G
value of the pixel i. Each R, G, B pixel value is then multiplied by this factor.
3.2 Modelling data
1.
A suitable regression procedure is then used to model the image R, G, B data to the
corresponding measured CIELAB data, L*m , a*m , bm* . This requires the solution to the
equations:
L*m a1 Ra2 Ga3 B a4 RG a5 RB a6 GB a7 R 2 a8G 2 a9 B 2  k a
a m* b1 Rb2 G b3 B b4 RG b5 RB b6 GB b7 R 2 b8 G 2 b9 B 2  k b
bm* c1 R c 2 G  c3 B c 4 RG c5 RB c6 GB c7 R 2 c8 G 2 c3 B 2  k c
It is convenient to carry out these calculations using Microsoft Excel and the LinEst
Array Function can be used to implement linear and quadratic models. Higher order
regression models must be implemented using alternative software, for example, Matlab.
2.
The predicted CIELAB data, L*p , a*p , b*p , are then calculated using the parameters a1-9,
b1-9, c1-9 applied to the image R, G, B values. The suffix p refers to predicted values,
obtained using the model.
3.
A measure of the success of a particular model can be found by calculating the colour
difference between the measured data and that predicted using the model.
The differences in these parameters, L*, a*, b*, are calculated:
L*  L*m  L*p
a*  a*m  a*p
b*  bm*  b*p
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Good Practice Guide to the use of MAVIS II
*
m
*
m
*
p
*
m
*
p
*
p
where L ,a ,b and L ,a ,b are CIELAB parameters corresponding to the measured
data and predicted data respectively.
*
The colour difference, E ab
, can then be calculated for each colour patch using the
equation:

*
Eab
 L*   a*   b* 

2 1/ 2
2
To further reduce these data, a histogram can be plotted by assigning the values of colour
*
difference, E ab
, to bins of a defined size. This histogram data can then be used to
produce a cumulative frequency distribution. In a statistical sense, values of colour
difference are not normally distributed because they usually tend towards a value close to
zero. Thus, the average value is not the best measure of central tendency; a more correct
value is the median of the distribution and this can easily be calculated using the Quartile
Function in Excel. In addition, it is useful to know the maximum value of the colour
difference as an indication of the range: this can be calculated using the MAX Function in
Excel. An example histogram is shown in figure 5.
15
100
90
70
10
60
50
40
5
30
Cumulative Frequency (%)
80
Frequency of Occurrence
20
10
30
28
26
24
22
20
18
16
14
12
10
8
6
4
0
2
0
0
5.
2
CIELAB Colour Difference
*
Figure 5. A histogram of values of CIELAB colour difference, E ab
, obtained
using a 24-patch GretagMacbeth ColorChecker chart, using L*, a*, b* input data.
Also shown is the associated cumulative frequency distribution.
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Good Practice Guide to the use of MAVIS II
6.
As a rule-of-thumb, a median value of colour difference of less than 3 and a maximum
value of less than 10 has been found to be acceptable.
7.
In order to produce a reasonable characterisation for some cameras it has been found
useful to implement a ‘gamma correction’ to the data to optimise the results of the
regression models. The best way to implement this function is to use the following
function:
R'  R 1 / 
where the R pixel value is corrected to a new value R’, with similar expressions for G’
and B’. Note that the same value of  is used in all three channels. The optimum value of
 can be found using the Excel Goal Seek Function to optimise the final median value of
colour difference obtained from the distribution of values for the coloured patches
8.
To give confidence in the results it is also useful to plot separately the predicted L*, a*
and b* values against their corresponding input values. The required results are straight
lines through the data points. Figure 6 shows an example of these plots.
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Good Practice Guide to the use of MAVIS II
100.0
Predicted L*
80.0
60.0
40.0
20.0
0.0
0.0
20.0
40.0
60.0
80.0
100.0
Original L*
100.0
80.0
Predicted a*
60.0
40.0
20.0
0.0
-60.0 -40.0 -20.0 0.0
-20.0
20.0 40.0 60.0 80.0 100.0
-40.0
-60.0
Original a*
100.0
80.0
Predicted b*
60.0
40.0
20.0
0.0
-60.0 -40.0 -20.0 0.0
-20.0
20.0 40.0 60.0 80.0 100.0
-40.0
-60.0
Original b*
Figure 6. Predicted CIELAB coordinates calculated using a quadratic model and
plotted as a function of their corresponding measured values.
Upper plot– L* value, middle plot – a* value: lower plot – b* value.
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Good Practice Guide to the use of MAVIS II
4. SUMMARY
The main factors to be aware of when using this instrument can be summarised as follows:
i) Camera settings. Before taking any wound images make sure that the camera settings are
correct, for example exposure time 1/350, ISO equivalent setting 800, 'M'anual dial setting,
flash on. Although the measurement program will identify set-up mistakes this can only be
done after images have been taken.
ii) Calibration check. The calibration of the instrument should be checked (using the blue
consistency checker) at regular intervals, ideally at the start of every measurement session,
but definitely once a week or after the instrument was subjected to shocks or rough handling.
iii) Positioning. Although the target light system will guide users with respect to the correct
distance between instrument and wound and helps to position the lesion in the image centre,
the user should be aware that best results are achieved only when the instrument is pointed
perpendicularly towards the wound.
iv) Accuracy and precision limitations. Users should be aware that although results are shown
with one or two digits after the decimal point, these apparently precise figures do not reflect
the true accuracy or precision of the system. These depend on a variety of factors, mainly the
ability of the user to repeatedly delineate the wound in a consistent way and the area/volume
ratio of the wound itself. (2,3)
v) The colour reproduction of an image obtained using the MavisCal II camera will appear to
be satisfactory without using the camera colour characterisation procedure. In order to
generate image data that relate to CIE colorimetry however, it is essential that the camera
characterisation procedure be followed. For consistent use over time it is necessary to apply
the characterisation procedure at regular intervals.
5. REFERENCES
1) Pointer M R. MAVISCAL: Digital Camera Calibration for Wound Measurement –
Colour Characterisation. NPL Report DQL-OR 014, June 2006.
2) Plassmann P, Jones T D. MAVIS - A non-invasive instrument to measure area and
volume of wounds. Medical Engineering and Physics, 20 (1998), p.325-331
3) Jones TD, Plassmann P. An active contour model for measuring the area of leg ulcers,
IEEE Transactions on Medical Imaging, December 2000, vol.19, Issue 12, p.12021210
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Good Practice Guide to the use of MAVIS II
APPENDIX 1 - DIMENSIONAL CALIBRATION AND MEASUREMENTS
The initial calibration of the MAVIS system is carried out by Isotec Imaging Ltd. Images of
printed grids are positioned at a range of distances and recorded to give the dimensional
calibration. To verify the dimensional measurements made by MAVIS II, metal artefacts with
machined depressions ranging in area and volume have been developed by NPL. These are
measured using a high precision coordinate measuring machine and the areas and volumes of
the depressions calculated to a high precision.
A1.1 Initial calibration of MAVIS system
The initial calibration is carried out by imaging a grid of regularly spaced lines printed on paper.
Stereo pairs of images, such as shown in figure 7, are digitised and analysed using a special
algorithm that recognises common points in image pairs.
Figure 7. A stereo image of a printed grid taken with MAVIS II during calibration
The camera system is mounted on a camera stand such that the centre of the grid is 800 mm
from the front of the digital camera’s detector array and appears in the centre of the right
image. The point in the centre of the grid is the zero point of the 3D reference frame. The
instrument is moved towards and away from the grid over a depth range of -150 mm to
+150 mm from the reference frame and 13 images are taken at regular intervals over the
300 mm range.
The disparity of a point between the left and right images is measured in pixels for the 13
image pairs, varying in depth. The disparity is plotted against depth and a 2nd order
polynomial curve is fitted, shown in figure 8. For each calibration image the number of pixels
per millimetre is calculated along the X- and Y-axis and plotted against disparity. Again, 2nd
order polynomial curves are fitted.
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Good Practice Guide to the use of MAVIS II
Left - Right Disparity Against Depth
Depth(mm)
200
150
y = 0.0039x2 + 2.2929x + 106.52
R2 = 0.9996
100
50
0
-160
-140
-120
-100
-80
-60
-40
-20
-50
0
20
40
-100
-150
-200
Disparity(pixels)
Figure 8. Estimation of the polynomial function used to calculate the
depth of a point to give its left-right disparity.
Given the left-right disparity of a point in the right image, its X, Y and Z (depth) coordinates
can be calculated in millimetres.
All points in the right image that are successfully matched with the left image are plotted in
the 3D reference frame in millimetres. Points are connected to their neighbours by the process
of Delaunay Triangulation to form a surface. The surface is smoothed to remove outlying
points by median filtering and averaging of neighbouring points.
As the data smoothing stage will lead to a slight shrinkage of the surface the system is likely
to underestimate the surface area and further underestimate the volume.
A1.2 Dimension traceability using calibration artefacts
Special dimensional calibration artefacts are used to scale the camera system and these were
developed during the MavisCal project. An example, shown in figure 9, is a metal plate
100 mm x 100 mm x 20 mm. The plate has a high precision concave shape formed on the
upper surface using a 5-axis machine tool. A pad-printing technique was used to coat the
concave surface with a pattern of squares of varying grey levels. MAVIS II employs special
software which scans both captured images, and the patterns enable them to be matched up
before the software then computes the wound dimensions. To create a highly defined
transition a blue coloured metal ring, also visible in figure 9, was inserted between the flat
surface of the artefact and the coated surface.
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Good Practice Guide to the use of MAVIS II
Figure 9 Dimensional calibration artefact
Figure 10 Non-contact coordinate measuring machine
The shape of the concave surface was measured with a high precision non-contact coordinate
measuring machine fitted with a vision probe, shown in figure 10. The machine employs laser
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Good Practice Guide to the use of MAVIS II
interferometry and provides measurements traceable to national standards. The perimeter of
the concave surface in the X-Y plane was located using optical edge detection tools, whereas
the depth (Z) was detected by repeatedly focusing a small beam of light on to the coated
surface as the artefact was traversed in 0.1 mm steps across a selected diameter. From these
measurements the area and volume of the calibration artefacts were computed.
The calibrated artefacts are then measured using MAVIS II and the results compared. A range
of artefacts has been produced as shown in figure 11 and typical dimensions are listed in
table 1.
Figure 11. A range of dimensional calibration artefacts
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Good Practice Guide to the use of MAVIS II
Depression
Diameter
mm
60
60
60
60
50
50
50
40
Radius of
Curvature
mm
450.5
151.5
78
54
313
80.13
43.06
42.5
Depression Depression Depression
Depth
Volume
Area
3
mm
cm
cm2
1
1.41
28.3
3
4.26.
28. 6
6
8.60
29.4
9
13.12
30.8
1
0.98
19.7
4
3.96
20.1
8
8.12
21.6
5
5.29
14.6
Table 1. Typical dimensions of artefacts produced for MAVIS II
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