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A Prototype Optical Tracking System Investigation and Development - page 121 / 170

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8.2 Black Spot module testing (2D testing)

107

0.035

0.035

0.03

Standard deviation X (pixels)

0.03

0.025

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0.015

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0.005

Standard deviation Y (pixels)

0.025

0.02

0.015

0.01

0.005

00

100

200

300 400 X (pixels)

500

600

700

00

100

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300 400 X (pixels)

500

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(a)

(b)

Figure 8.7 These graphs plot the centroid variation versus X position for a band of markers with similar Y values. a) shows the standard deviation in X and b) shows the standard deviation in Y.

position were used. This was an attempt to remove any bias that could be caused by using a varying Y position. Figure 8.7 shows the outcome. The graphs have the same shape and similar quadratic curves provide a good fit to the data. better test would be to use data from just one marker as it is translated across the entire FOV and is suggested as future

work.

stationary measurement was taken and the mean marker position was plotted with error bars (Figure 8.8). The error bars represent the standard deviation of the marker position

and are increased 1000× so that they can be seen on this graph. This provides an overview of the parts of the FOV that appear to give better results. The six markers on the right have larger standard deviations than the markers in the middle. This agrees with the results in Figures 8.6a,b as these markers are near the outside of the FOV. The markers in red with a square box are those that have intensities below 80. The large standard deviations in these markers could be due to the low intensity so should not be considered. similar data set that had a larger range in Y values was analysed and the results support that shown in

Figure 8.8.

Using these results it is concluded that good results can be obtained by using markers in a region between approximately 100 < X < 500 based on Figures 8.6a, b. In this region all standard deviations are within 25% of the minimum. s the rail was translated in the X direction it was difficult to find a trend in the Y direction. The quadratic curves fitted to

these figures are

σX(X) = 61.6 × 10

9X

2

37.9 × 10

6X + 16.3 × 10

3

,

(8.4)

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