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B-Spline Curve Approximation by Utilizing Big Bang-Big Crunch Method

Özkan inik1,∗, Erkan Ülker2, ismail Koç2

1 Department of Computer Engineering, Gaziosmanpa¸sa University, Tokat, Turkey
2 Department of Computer Engineering, Konya Technical University, Konya, Turkey

* Corresponding Author:Özkan inik, email

Computer Systems Science and Engineering 2020, 35(6), 431-440. https://doi.org/10.32604/csse.2020.35.431

Abstract

The location of knot points and estimation of the number of knots are undoubtedly known as one of the most difficult problems in B-Spline curve approximation. In the literature, different researchers have been seen to use more than one optimization algorithm in order to solve this problem. In this paper, Big Bang-Big Crunch method (BB-BC) which is one of the evolutionary based optimization algorithms was introduced and then the approximation of B-Spline curve knots was conducted by this method. The technique of reverse engineering was implemented for the curve knot approximation. The detection of knot locations and the number of knots were randomly selected in the curve approximation which was performed by using BB-BC method. The experimental results were carried out by utilizing seven different test functions for the curve approximation. The performance of BB-BC algorithm was examined on these functions and their results were compared with the earlier studies performed by the researchers. In comparison with the other studies, it was observed that though the number of the knot in BB-BC algorithm was high, this algorithm approximated the B-Spline curves at the rate of minor error.

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Cite This Article

. Inik, E. Ülker and I. Koç, "B-spline curve approximation by utilizing big bang-big crunch method," Computer Systems Science and Engineering, vol. 35, no.6, pp. 431–440, 2020.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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