MAVIS II Good Practice Guide - University of Wales,...

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.

Good Practice Guide to the use of MAVIS IIhttp://www.glam.ac.uk/socschool/research/medical_imaging/index.php

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July 2006


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 1DL2) Enabling Metrology Division, National Physical Laboratory, Teddington, TW11 0LW3) Quality of Life Division, National Physical Laboratory, Teddington, TW11 0LW4) 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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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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http://www.npl.co.uk/measurement_for_innovators


TABLE OF CONTENTS

Acknowledgements............................................................................................................... iii

1. INTRODUCTION............................................................................................................ 11.1 Background........................................................................................................ 11.2 MAVIS II............................................................................................................ 2

2. GUIDE TO USING THE INSTRUMENT......................................................................42.1 Switching On...................................................................................................... 42.2 Taking Images.................................................................................................... 42.3 Downloading Images to PC from CF Memory Card.......................................52.4 Making measurements using the MAVIS Software.........................................5

2.4.1 Selecting the image to measure...........................................................52.4.2 Drawing around the wound perimeter...............................................62.4.3 Inspecting results.................................................................................62.4.4 Saving results.......................................................................................7

2.5 Database functions............................................................................................. 72.5.1 Main Screen: “Measured Images”.....................................................72.5.2 Results window....................................................................................82.5.3 Tools to correct saving mistakes.........................................................8

2.6 Software installation..........................................................................................92.6.1 System check........................................................................................ 92.6.2 Install/Uninstall...................................................................................92.6.3 Setup.................................................................................................. 10

2.7 Changing the Target Light Battery.................................................................102.8 Recharging the camera battery.......................................................................112.9 Calibration Check............................................................................................11

3. DIGITAL CAMERA CALIBRATION - COLOUR CHARACTERISATION..........123.1 Practical procedure..........................................................................................123.2 Modelling data.................................................................................................. 13

4. SUMMARY.................................................................................................................... 17

5. REFERENCES............................................................................................................... 17

APPENDIX A1 - DIMENSIONAL CALIBRATION AND MEASUREMENTS.............17A1.1 Initial Calibration of MAVIS system...........................................................18A1.2 Dimension traceability using calibration artefacts......................................19

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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..................................12Figure 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 giveits 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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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

In addition to being painful, these invasive procedures may carry a risk of cross-infection.

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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, non-invasively. 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. 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

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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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2. GUIDE TO USING THE INSTRUMENT

This section reproduces instructions from the instrument guidebook.

2.1 Switching On

2.2 Taking Images

2.3 Downloading Images to PC from CF Memory Card

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Slide lever into ‘ON’ positionSet Dial to position ‘M’Switch Flash onCheck batteries:Camera charged?Orange Flash light on?Target Lights working?

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.


2.4 Making Measurements using the MAVIS Software

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2.4.1 : Selecting the image to measure

1. Select image

2. Click the ‘Measure’ button

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.

Drag rectangle to move the zoomed area

2.4.2: Drawing around the wound perimeter


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Zoom in

Zoom out

Remove last point(s) set

Click on perimeter to

set pointsBack to

Main Menu

When contour is closed click ‘Next’ to start calculations.

Drag this corner to adjust window size

Click the button to continue.

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.

2.4.3: Inspecting results

EXISTING PATIENT

1. Select patient

2. Select wound3. Click on ‘Save results’

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”

A2.4.4: Saving results

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2.5 Database Functions

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2.5.1: Main Screen: “Measured Images”

Select wound

Select patient

Show:TableGraphPlotGallery

Delete selected wound or patient data

View image in 3D

Measure again

Delete image shown

Browse through wound images

2.5.2: Results window

Results can be copied to clipboard

for pasting into Word or Excel


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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.


2.6 Software Installation

2.6.1: System Check

2.6.2: Install / Uninstall

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Hardware (minimum requirements):Operating System: Windows 98 or later Processor: 1.5 MHz RAM: 500 MBHard Disk Space: 100 MB Screen Resolution: 1024 x 768

DirectX requirementsRun 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

Installation:1. Insert CD into CD ROM drive2. (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).


2.6.3: Setup

2.7 Changing the Target Light Battery

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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.

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)


2.8 Recharging the Camera Battery

2.9 Calibration Check

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Move right projector half downwards to access battery.Open camera battery compartment.Click orange lever to remove batteryInsert battery into charger

NOTE: Charging is completed when the red light has stopped flashing.

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.


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, , and CIELAB colorimetric coordinates, , calculated.

Target L*, a *, b *

Im age R , G , B

Model

P red icted L *, a *, b *

Co lour d iffe rence, E *

G am m a correct

Digita l cam era+

electron ic flash

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.

3. The R, G, B values for each of the pixels in the two images then need to be obtained. To do this, software is required that can open the image and calculate average R, G, B

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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:

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, . This requires the solution to the equations:

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, , 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:

where and are CIELAB parameters corresponding to the measured data and predicted data respectively.

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The colour difference, , can then be calculated for each colour patch using the equation:

5. To further reduce these data, a histogram can be plotted by assigning the values of colour difference, , 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.

0

5

10

15

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

CIELAB Colour Difference

Freq

uenc

y of

Occ

urre

nce

0

10

20

30

40

50

60

70

80

90

100

Cum

ulat

ive

Freq

uenc

y (%

)

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.

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

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regression models. The best way to implement this function is to use the following function:

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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0.0

20.0

40.0

60.0

80.0

100.0

0.0 20.0 40.0 60.0 80.0 100.0

Original L*

Pred

icte

d L*

-60.0

-40.0

-20.0

0.0

20.0

40.0

60.0

80.0

100.0

-60.0 -40.0 -20.0 0.0 20.0 40.0 60.0 80.0 100.0

Original a*

Pred

icte

d a*

-60.0

-40.0

-20.0

0.0

20.0

40.0

60.0

80.0

100.0

-60.0 -40.0 -20.0 0.0 20.0 40.0 60.0 80.0 100.0

Original b*

Pred

icte

d 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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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.1202-1210

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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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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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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

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laser 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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Depression Diameter

mm

Radius of Curvature

mm

DepressionDepthmm

DepressionVolume

cm3

DepressionAreacm2

60 450.5 1 1.41 28.360 151.5 3 4.26. 28. 660 78 6 8.60 29.460 54 9 13.12 30.850 313 1 0.98 19.750 80.13 4 3.96 20.150 43.06 8 8.12 21.640 42.5 5 5.29 14.6

Table 1. Typical dimensions of artefacts produced for MAVIS II

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