Vectorizing outlines of generic shapes by cubic spline using simulated annealing

Abstract

A global optimization technique is proposed for the outline capture of generic shapes. This is inspired by a global optimization algorithm based on simulated annealing (SA) by Kirkpatrick et al. [S. Kirkpatrick, C.D. Gelatt Jr., and M.P. Vecchi, Optimization by simulated annealing, Science 220(4598) (1983), pp. 671–680]. The proposed work, in this paper, is concerned with an efficient technique of vectorizing outlines of generic shapes. It is mainly achieved by curve fitting with a generalized cubic spline. The overall technique has various phases including extracting outlines of images, detecting corner points from the detected outline, curve fitting and addition of extra knot points if needed. The last two phases make a significant contribution by making the technique automated. It uses the idea of SA to optimize the shape parameters in the description of the generalized cubic spline introduced. The idea of SA has been used to optimize the shape parameters in the description of the generalized cubic spline introduced. The spline method ultimately produces optimal results for the approximate vectorization of the digital contour obtained from the generic shapes. The process is fully automatic and requires no human intervention. Implementation details are sufficiently discussed. Some numerical and pictorial results are also demonstrated to support the proposed technique.

Keywords:

• generic shapes
• curve fitting
• cubic spline
• simulated annealing
• knot insertion

Acknowledgements

This work was supported by Kuwait University, Research Grant No. [WI 01/08].