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Estimating Criteria for Fitting B-spline Curves: Application to Data Compression

Éric Saux, Marc Daniel

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Abstract

In this paper, we analyse the different parameter choices for fitting B-spline curves. New estimating criteria for data approximation are introduced in order to estimate the results. The definitions of norms correspond to a global analysis of the curve. Other criteria are based on a local analysis. We present a new method for data compression using fitting B-splines and compare it to usual ones. Keywords: Data compression, estimating criteria, fitting B-splines.

About this research paper

What this paper is about

In this paper, we analyse the different parameter choices for fitting B-spline curves. New estimating criteria for data approximation are introduced in order to estimate the results. The definitions of norms correspond to a global analysis of the curve. Other criteria are based on a local analysis. We present a new method for data compression using fitting B-splines and compare it to usual ones. Keywords: Data compression, estimating criteria, fitting B-splines.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In this paper, we analyse the different parameter choices for fitting B-spline curves. New estimating criteria for data approximation are introduced in order to estimate the results. The definitions of norms correspond to a global analysis of the curve. Other criteria are based on a local analysis. We present a new method for data compression using fitting B-splines and compare it to usual ones. Keywords: Data compression, estimating criteria, fitting B-splines.

Key concepts: Curve fitting, Spline (mechanical), B-spline, Surface fitting, Data compression, Computer science, Applied mathematics, Mathematics

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