Optimizing the Shape Parameters of Beta-Spline Using Particle Swarm Optimization

  • Authors

    • Sharifatul Aniza Suliman
    • Normi Abdul Hadi
    2018-12-09
    https://doi.org/10.14419/ijet.v7i4.33.23492
  • Beta-Spline, Curve Fitting, Particle Swarm Optimization, Shape Parameters, 2D Font Image.

  • Abstract

    Beta-spline is an alternative curve for 2D font representation. It is preferred since it has G2 continuity and two shape parameters, that can be used to control the curve shape. These shape parameters can also be used to optimize the error between fitted curve and original data points. Commonly, most of the researcher use value of shape parameters of beta-spline as and  or some of the researcher choose any random value of these two shape parameters that suitable to be used in beta-spline curve fitting. The values of shape parameters are very important since the values affect the total error of the fitted curves. Thus, in this paper, Particle Swarm Optimization (PSO) is employed to determine the optimum value of the two shape parameters that will optimize the approximation error of the fitted curve. The technique is applied on two fonts: ى and δ, and tested using various number of iterations and populations.

     

     

     

  • References

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  • How to Cite

    Aniza Suliman, S., & Abdul Hadi, N. (2018). Optimizing the Shape Parameters of Beta-Spline Using Particle Swarm Optimization. International Journal of Engineering & Technology, 7(4.33), 93-97. https://doi.org/10.14419/ijet.v7i4.33.23492

    Received date: 2018-12-08

    Accepted date: 2018-12-08

    Published date: 2018-12-09