Data fusion of areal measured microtopographies with plane of reference using optical sensors

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The overarching goal of the project is the automation of overlapping measurements of technical surfaces using image processing microscopes and subsequent fusion for the creation of high resolution surface data sets with larger lateral dimensions and minimized measurement uncertainty (automated stitching). Methods for the reduction of the measurement uncertainty of single measurements by adaptive lighting are to be researched as well as methods for the minimization of the uncertainties of stitching (registration errors, surface deviations through data fusion). By the means of measurement controlled by image processing the uncertainty of the merged fields of measurement is minimized during the measurement to make sure the quality criteria are met.In the step, the methods developed in the previous phase of the project are to be validated and improved using measurements of different technical surfaces to allow an evaluation in dependence of the task of the measurement. Using simulated deviations on cut up single measurements and multiple measurements with positions controlled by high precision positioning systems the capabilities of our algorithms will be tested. As a final test we will compare the results of our methods with the stitching systems of the microscopes available to the institute. The measurement of technical surfaces exhibiting high gradients often includes missing data and outliers due to data processing errors or insufficient lighting. These measurements are usually interpolated to complete the surface data set. Interpolated points of measurement always depend on their surroundings, the used interpolation method and the method of measurement. By adapting the lighting (intensity, spectrum) to the measured surface and re-measuring and subsequent data fusion the quality of the measurement can be increased. Thus the amount of false measurement points can be reduced greatly by measurement controlled by image processing.The concept of measurement controlled by image processing can also be applied to the measurement of overlapping surface areas for subsequent image registration and fusion using image processing techniques. Prior measurements are to be used to estimate the ideal translation distance to allow for an image registration with minimized registration error. This is to be accomplished by using an overview measurement (using lower resolutions and larger measurement areas than the intended measurement) and by extrapolation of the current high resolution measurement. By means of these techniques we want to automatize stitching measurements with a guaranteed measurement and positioning uncertainty.