Curve and surface modeling with uncertainties using dual Kriging

This paper presents a new technique bases on dial Kriging interpolation for modeling curves and surfaces in the presence of uncertainties in data poin ts. Uncertainties result from measurement errors; therefore, a direct appli cation of this method is found in curve/surface modeling using discrete set s of digitized points. It focuses on a common problem in geometric modeling , the trade-off between curve/surface smoothness and the approximation erro rs. The Kriging model filters the noise in the data while controlling the d eviation locally at each point. However, the classical least-squares techni que minimizes the average deviation, hence allowing only a global control o f the model. The presented method generates smoother and more accurate repr esentation of the actual curve or surface. It has potential applications in reverse engineering, NC machining, computer-aided inspection and tolerance analysis and verification. Examples of a computer mouse and a portion of t he hood of a scaled-down car are presented for illustration.