Optimal Multilevel Thresholds based on Tsallis Entropy Method using Golden Ratio Particle Swarm Optimization for Improved Image Segmentation

This paper proposes a novel method of Particle Swarm Optimization, called Golden Ratio Particle Swarm Optimization (GRPSO), based on Golden Ratio found in nature. GRPSO is used for determining optimal thresholds for improved image segmentation. The thresholding problem is treated as an optimization problem with an objective function based on Tsallis Entropy method. Improved performance of GRPSO in image segmentation is established by comparison of objective values achieved by GRPSO with those achieved by Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Bacterial Foraging (BF) Algorithm.