No abstract

White-light interferometry (WLI) on rough surfaces is based on interference from individual speckles. The measurement uncertainty of WLI is limited by a random shift of these individual interference patterns. The statistical error in each measurement point depends on the brightness of the corresponding speckle: a dark speckle yields a larger error than a bright speckle. In this paper, a novel method is presented to reduce the measurement uncertainty significantly: by sequentially switching the direction of the illumination, the camera sees several independent speckle patterns in sequence. From each pattern, the brightest speckles are selected to eventually calculate an accurate height map. This height map displays no outliers, and the measured surface roughness is close to the stylus measurements.

In white-light interferometry at rough surfaces ("Coherence radar") the measuring uncertainty is physically limited by the arbitrary phase of the individual speckle interferograms. As a consequence, the standard deviation of the measured shape data is inevitably given by the (optically unresolved) roughness of the surface. The statistical error in each measuring point depends on the brightness of the corresponding speckle; a dark speckle yields a more uncertain measurement than a bright one. If the brightness is below the noise threshold of the camera, the measurement fails completely and an outlier occurs. We present a new method to significantly reduce the measuring uncertainty and the number of outliers. We achieve this by generating several statistically independent speckle patterns, by use of different directions of the illumination. We evaluate the different measurements and select the best measurement or assign more weight to brighter speckles.

In the poster a project is presented that investigates the efficiency of using educational robots in early secondary computer science education. Results will be obtained from a comparative study in 9 th grade informatics classes.