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Indexed by:期刊论文

Date of Publication:2022-06-28

Journal:图学学报

Affiliation of Author(s):数学科学学院

Volume:39

Issue:2

Page Number:287-294

ISSN No.:2095-302X

Abstract:The use of progressive iterative approximation (PIA) to fit data points has received a deal of attention benefitting from its simplicity and flexibility. To obtain a fitting curve satisfying the shape high fidelity, we present an adaptive B-spline curve fitting algorithm based on regularized progressive iterative approximation (RPIA) and the selection of dominant points. Firstly, the initial dominant points are selected from the given points in terms of curvature estimates and an initial progressive iterative approximation curve is constructed. Then the fitting curve based on RPIA is updated by means of the fitting error and the selection of refinement dominant points according to the curvature distribution of given points. The fitting curve possesses fewer control points at flat regions but more at complex regions. By the use of a regular parameter, progressive iterative approximation is generalized and the flexibility of PIA is promoted. Finally, numerical examples are provided to demonstrate that compared with the conventional least square approaches the proposed method can achieve a higher fitting precision with far fewer control points.

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