Dimensional Measurement using Vision Systems - NPL Publications ...

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
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