Image Clustering Method based on Particle Swarm Optimization
Igor Vitalievich Kotenko, Iuliia Kim, Anastasia Matveeva, Ilya I. Viksnin · Annals of Computer Science and Information Systems · 2018
To implement efficient computer vision mechanisms, efficient image clustering methods are important.The paper elaborates a clustering method based on particle swarm optimization (PSO) which provides automatic establishment of clustering parameters.The developed PSO based clustering method was tested on 860 images for a car vision system and its results and contribution to the pattern recognition quality improvement were assessed in comparison with fuzzy C-means and k-means.The results do not differ significantly, but distinction in average time of work for these methods was noted.The PSO clustering method is faster than k-means and slower than fuzzy C-means.However, fuzzy C-means method does not guarantee correct results during the further analysis, so the PSO clustering method can be more efficient for implementation in computer vision systems.