This paper presents a novel method to increase the accuracy
of linear fitting of implicit polynomials. The proposed
method is based on the 3L algorithm philosophy. The novelty
lies on the relaxation of the additional constraints, already
imposed by the 3L algorithm. Hence, the accuracy of
the final solution is increased due to the proper adjustment
of the expected values in the aforementioned additional constraints. Although iterative, the proposed approach solves the fitting problem within a linear framework, which is independent of the threshold tuning. Experimental results, both in 2D and 3D, showing improvements in the accuracy of the fitting are presented. Comparisons with both state of the art algorithms and a geometric based one (non-linear fitting), which is used as a ground truth, are provided.
Mohammad Rouhani and Angel D. Sappa