Abstract
When designing optical measurement systems, it is common to use cameras, lenses and frame grabbers specially designed for metrology applications. These devices are expensive, therefore optical metrology is not the technology of choice in low cost applications. On the contrary to this, surveillance video cameras and home oriented frame grabbers are cheap, but imprecise. Their use introduces inaccuracies in the measurements, that sometimes can be compensated by software. Following this last approach, in this paper it is proposed to use fuzzy techniques to exploit the tolerance for imprecision of a practical metrology application (to automate the measurement of vehicle dimensions in Technical Inspection of Vehicles in Spain, the equivalent of the Ministry Of Transport Test or MOT Test in UK) and to find an economic solution. It will be shown that a genetic algorithm (GA), guided by a fuzzy characterization of the sources of error, can optimize the placement of the video cameras in a station so that these mentioned sensors can be used to take measurements within the required tolerance.
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