DEVELOPMENT OF A CLONAL SELECTION ALGORITHM BASED SYSTEM FOR AUTOMATIC DETECTION OF MULTIPLE SHAPES

📄 Project Abstract

In this dissertation a Clonal Selection Algorithm (CSA) based system that detected multiple instances of circles, quadrilaterals and triangles in an image scene was developed. CSA models how B-cell antibodies of the immune system protect the body from invading antigens. The developed system eliminated the need for separate implementations of the CSA for detecting the different shapes in an image. The implementation of the system was done using MATLAB 2015a, the edges and corners in the image scene were first extracted using Canny edge and Harris corner detectors and the edge-only image was used as the antigen. A candidate solution was formed by random selection of three (3) edge points to form a circle, four (4) corner points to form a quadrilateral and three (3) corner points to form a triangle. The CSA iterated until either an optimal solution (fitness of 1.0) is attained or when a maximum of 100 iterations is reached. The antibodies with high fitness (above the set threshold of 0.9 ...