Efficient Edge Detection Using Fuzzy Heuristic Particle Swarm Optimization

Abstract

This paper presents a hybridization of Particle Swarm Optimization (PSO) and Fuzzy edge detector. The edge detector is used as the initial population and as the objective function. The purpose of hybridizing the algorithm is to create an optimized edge detector. Classical Fuzzy Heuristics (CFH) detects thick edges. These thick edges need to be optimized to obtain a thin line. In this research the PSO is used to optimize the edge detection detected by the CFH algorithm and it is referred to as FHPSO. The test images are radiographs images of the metacarpal. These images have been used, because there is a need to detect strong and thin edges. Radiograph images are noisy in nature, which makes it difficult to measure the cortical thickness, the cortical outline of the inner cortical and outer cortical of the long tubular bone. The outer cortical edges are considered to be the strong edges due to high discontinuity values and the inner cortical edges are considered weak edges due to low their discontinuity values. The performance of FHPSO in detecting edges has been shown to be quite efficient.