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W.-C. Hu, “Multiprimitive Segmentation Based on Meaningful Break Points for Fitting Digital Planar Curves with Line Segments and Conic Arcs,” Image and Vision Computing, Vol. 23, No. 9, 2005, pp. 783-789. doi10.1016/j.imavis.2005.05.004

has been cited by the following article:

• TITLE: Genetic Algorithm Works for Vectoring Image Outlines of Generic Shapes

  AUTHORS: Misbah Irshad, Muhammad Sarfraz, Malik Zawwar Hussain

  KEYWORDS: Spline; Approximation; Curve Fitting; Genetic Algorithm; Generic Shapes

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.6 No.7, June 28, 2013

  ABSTRACT: This work proposes a scheme which helps digitizing hand printed and electronic planar objects or vectorizing the generic shapes. An evolutionary optimization technique namely Genetic Algorithm (GA) is used to solve the problem of curve fitting with a cubic spline function. GA works well for finding the optimal values of shape parameters in the description of the proposed cubic spline. The underlying scheme comprises of various phases including data of the image outlines, detection of corner points, using GA for optimal values of shape parameters, and fitting curve using cubic spline to the detected corner points.