An Analytical Curvature B-Spline Algorithm for Effective Curve Modeling

  • Joi San TanEmail author
  • Ibrahim Venkat
  • Bahari Belaton
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9429)


This paper presents a new algorithm based on an analytical approach for generating non-uniform cubic B-spline which has potential applications in curve modeling. For a given set of data points, knot vectors are computed using the centripetal approach. Next, number of data points is assimilated around the high curvature areas and the parametrization aspect is computed by the inverse chord length with the new set of data points. Second order derivatives are used to determine the high curvature areas of the curves. The method proposed here enables to construct the curves smoothly around high curvature areas by assigning adequate number of data points for the B-splines. Experimental validations justify the fact that the average curve fitting error yielded by the proposed approach is the lowest when compared to other standard curve models.


Non-uniform cubic B-spline Centripetal method Second order derivative Inverse chord length 



This research is supported by the RU-PRGS Universiti Sains Malaysia (1001/PKOMP/846051) grant titled “Skull and Photo Superimposition with Conditional Anthropological Parameters using Computer Sciences.” and RUI grant (1001/PKOMP/811290). We would like to thank Prof. K.G Subramaniam for providing valuable comments to improve this paper.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.School of Computer SciencesUniversiti Sains MalaysiaPulau PinangMalaysia

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