Iterative algorithm for accurate superposition of contours with non-uniform sampling step

Abstract

In this article, we describe an iterative algorithm for accurate superposition of contours with non-uniform sampling step. The processing contours are characterized by the same shape, but the sampling step is non-uniform, with no matching between points of the superposed contours. This makes impossible the use of methods for estimating superposition parameters by matching points. The algorithm proposed herein allows estimating the offsets and rotation angle separately. The idea of the algorithm is to perform the iterative correction of parameters. An estimate of the offsets is used to estimate the rotation angle and, vice versa, an estimate of the rotation angle is used to estimate the offsets. The proposed algorithm is characterized by a higher speed of processing than a brute force algorithm and a lower estimation error than algorithms that analyze contour macroparameters.