H. Kano, H. Nakata, C. F. Martin, “Optimal Curve Fitting and Smoothing using Normalized Uniform B-Splines: A Tool for Studying Complex Systems”, Applied Mathematics and Computation, 2005, pp. 96-128.

has been cited by the following article:

• TITLE: Intelligent Approaches for Vectorizing Image Outlines

  AUTHORS: Muhammad Sarfraz

  KEYWORDS: Imaging; soft computing; vectorization; corner points; curve fitting

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.5 No.12B, January 18, 2013

  ABSTRACT: Two computing approaches, based on linear and conic splines, are proposed here in reviewed and extended for vectorizing image outlines. Both of the approaches have various phases including extracting outlines of images, detecting corner points from the detected outlines, and curve fitting. Interpolation splines are the bases of the two approached. Linear spline approach is straight forward as it does not have a degree of freedom.in terms of some shape controller in its description. However, the idea of the soft computing approach, namely simulated annealing, has been utilized for conic splines. This idea has been incorporated to optimize the shape parameters in the description of the generalized conic spline. Both of the linear and conic approaches ultimately produce optimal results for the approximate vectorization of the digital contours obtained from the generic shapes.