Reverse Engineering of Generic Shapes Using Quadratic Spline and Genetic Algorithm

Abstract

An approach, for reverse engineering of generic shapes is proposed which is useful for the vectorization of the generic shapes. The recommended scheme comprises of different steps including extracting outlines of images, identifying feature points from the detected outlines, and curve fitting. The quadratic spline functions are used to find the optimal solution of the curve fitting with the help of a soft computing technique genetic algorithm (GA), which gives best suitable values of shape parameters. Genetic algorithm, a technique, usually used to find the optimal solutions of bit-complicated problems has been utilized to calculate optimal values of parameters in the representation of quadratic spline, which give minimum error between detected boundary of the image and the fitted spline curve.