Dimensional Measurement using Vision Systems - NPL Publications ...

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Measurement Good Practice Guide No. 39 Figure 30: Array of spots used to determine image distortions and magnification errors. 7.6 SOURCES OF MEASUREMENT UNCERTAINTY If a vision system is being used as a comparator, then detailing the sources of uncertainty is straightforward. If the system is used for measurement, relying on the pixel calibration, then a little more work is required. The following two examples, which involve the measurement of dark features against a bright background, illustrate these two measurement approaches. It should be noted that vision systems are not restricted to just performing simple measurements on images of this kind alone, but can of course deal with images with far more complex features. The simple nature of the examples that follow is purely to give clarity to the analysis of the sources of uncertainty. Firstly, let us consider a vision system used as a comparator to measure the diameters of a series of spots, ranging in size from 3-48 µm. The calibration standard is an identical series of spots, the diameters of which have been calibrated and are traceable to the national standard of length. The spots were measured using a Leitz Ergolux AMC microscope with a 100x objective, a 1024x1024 square pixel Pulnix digital camera and a Leica QM550 CW image analyser. As this is a comparative measurement, the detection threshold is set at 50% of the camera grey scale. Before each unknown spot is measured, the vision system must be used to measure the calibration standard. This calibration gives the measurement its traceability. The same software routine is used for both the known (calibration standard) and unknown (test) spots with each spot measured three times in the same position in the image. This means that any errors, perhaps due to the effects of distortions or magnification, will be seen in 53
Measurement Good Practice Guide No. 39 the standard deviation of the measurements. The Equivalent Circle Diameter was measured, which is the diameter of a perfectly round circle derived from the area of the detected spot. This measurement is preferable to feret (calliper) measurements as it effectively gives sub-pixel accuracy. The deviation of the measurements on the calibrated spots from the true values gives the calibration offsets, as shown in Table 8 and graphically, in Figure 31. Table 8: Results from measurement of the calibration standard. Spot Run 1 Run 2 Run 3 Standard deviation Average Certified values Offset 1 47.839 47.841 47.849 0.005 47.843 47.66 -0.183 2 33.716 33.718 33.721 0.003 33.718 33.57 -0.148 3 23.794 23.8 23.807 0.007 23.800 23.65 -0.150 4 16.785 16.792 16.799 0.007 16.792 16.62 -0.172 5 11.805 11.807 11.809 0.002 11.807 11.63 -0.177 6 8.238 8.248 8.258 0.010 8.248 8.08 -0.168 7 5.782 5.782 5.79 0.005 5.785 5.61 -0.175 8 4.003 4.018 4.023 0.010 4.015 3.84 -0.175 9 2.738 2.746 2.755 0.009 2.746 2.57 -0.176 All dimensions in µm. OFFSET (µm) 0 -0.02 -0.04 -0.06 -0.08 -0.1 -0.12 -0.14 -0.16 -0.18 -0.2 0 10 20 30 40 50 y = 0.0002x - 0.1722 SPOT DIAMETER (µm) Figure 31: Calibration offsets, with the coefficients of the linear fit displayed. The unknown spots were then measured three times in exactly the same way, without changing the illumination conditions. The measured diameters were corrected using a linear fit applied to the calibration offsets, thereby giving the true diameters of the 54
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