Parallel Genetic Algorithm for Color Image Segmentation


This paper presents a Parallel Genetic Algorithm (PGA) based on the distributed (island) paradigm to optimize color image segmentation. The goal of using PGA is to accelerate the process of segmentation. However, that is not the only motivation for parallelism. Even when speed is not primary factor, these distributed algorithms, and as we shall see through the results, often outperform GAs with single population. Some examples in color images are presented and overall results discussed.