Edge detection using ant algorithms

Abstract

In this paper a new algorithm for edge detection using ant colony search is proposed. The problem is represented by a directed graph in which nodes are the pixels of an image. To adapt the problem, some modifications on original ant colony search algorithm (ACSA) are applied. A large number of experiments are employed to determine suitable algorithm parameters. We drive an experimental relationship between the size of the image to be analyzed and algorithm parameters. Several experiments are made and the results suggest the effectiveness of the proposed algorithm.

Multi-threading based implementation of Ant-Colony Optimization algorithm for image edge detection

“…The edge detection using ant algorithms is introduced in [15] where authors introduce the concept of using the pheromone matrix for detection of edges. They perform local and global updates on matrices according to the steps of different ants.…”

An Optimal Edge Detection Using Gravitational Search Algorithm

“…1). Information required to find out whether a pixel is an edge pixel or not is determined by the local statistics at that position [17]:…”

“…1) around the pixel (x, y) . It depends on the variation of the intensity values on the local group, and is given by [17] …”

Microscopic Image Analysis of Nanoparticles by Edge Detection Using Ant Colony Optimization

“…There are eight possible neighboring pixels surrounding the central pixel at (x,y). The η i,j is calculated as [15] …”