Uncertainty characterization in image-based measurements: A preliminary discussion

There are a large number of application fields where measurements deriving from digital images can assume a great relevance. Nevertheless, to make a p rofitable use of such measurements, it is indispensable to achieve a comple te and quantitative control on uncertainties that real systems introduce al ong the chain of steps going from real-world objects to the results of the measurement process, This paper deals with this nontrivial task and, in par ticular, with the analytical expression of uncertainty characterizing the r esults of image processing software. At first, a simplified model of uncert ainty of digital images is derived and experimentally tested; then the Cann y edge detector output uncertainty is analytically expressed and verified b oth in artificial and real-world images.