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. X-ray computed tomography as a measurement system faces some difficultiesconcerning the quality of the acquired measurements due to energy-dependentinteraction of polychromatic radiation with the examined object at hand.There are many different techniques to reduce the negative influences ofthese artefact phenomena, which is also the aim of this newly introducedmethod. The key idea is to create several measurements of the same object,which only differ in their orientation inside the ray path of the measurementsystem. These measurements are then processed to selectively correct faultysurface regions. To calculate the needed geometrical transformations betweenthe different measurements with the goal of a congruent alignment in onecoordinate system, an extension of the iterative closest point (ICP)algorithm is used. To quantitatively classify any surface point regarding itsquality value to determine the individual need of correction for each point,the local quality value (LQV) method is used, which has been developed at theInstitute of Manufacturing Metrology. Different data fusion algorithms arepresented whose performances are tested and verified using nominal–actualcomparisons.

Data fusion of surface data sets of X-ray computed tomography measurements using locally determined surface quality values