Edge detection through the use of a combined genetic algorithm-linear technique approach

Abstract

Image enhancement applications are highly dependent on the efficiency of edge detection techniques. This paper presents a new method, which combines the random search mechanisms of Genetic Algorithms with linear time methods. The GA establishes candidate areas as edge containers. Such areas are then investigated by using near-neighbor linear techniques for edge identification and detection. The resulting edge detection process approaches linear time complexity as demonstrated in the experiments.

A study of Edge Detection Techniques for Segmentation Computing Approaches

“…An iteration of the algorithm is basically equivalent to a generation in the evolutionary process. [11] Mainly, a genetic algorithm consists of three most important operations. They are Selection, Crossover and Mutation.…”