A novel evolutionary approach for 2D shape matching based on B-spline modeling

Shape representation plays a vital role in any shape optimization exercise. The ability to identify a shape with good performance is largely dependent on the underlying shape representation scheme. In this paper, a novel shape representation scheme is presented based on B-splines, wherein the control points representing the shape are repaired and subsequently evolved within the framework of a memetic algorithm. The underlying memetic algorithm is a multi-feature hybrid that combines the strength of a real coded genetic algorithm, differential evolution and a local search. Two test problems on shape matching are presented and solved using a mere 5000 function evaluations to illustrate the efficiency of the proposed scheme.