IMAGE CLASSIFICATION USING PARTICLE SWARM OPTIMIZATION

摘要

In this chapter, a new unsupervised image clustering approach which is based on the particle swarm optimization (PSO) algorithm is presented. The algorithm finds the centroids of a user specified number of clusters, where each cluster groups together similar pixels. The new image clustering algorithm has been applied successfully to three types of images to illustrate its wide applicability. These images include synthetic, MRI and Satellite images. A comparison between the new approach and the well-known K-means clustering algorithm is provided to show the efficiency of PSO in the area of image clustering.