Improved Particle Swarm Optimization Algorithm in Multilevel Image Thresholding

The principal challenge addressed in this paper is modifying the standard particle swarm optimization algorithm to achieve improved multilevel image thresholding performance. In this paper, a multilevel image thresholding method that relies on Kapur's entropy and the improved particle swarm optimization algorithm is presented. The improved particle swarm optimization algorithm employs a particular nonlinearly decreasing inertia weight strategy and Gaussian mutation. The performance of the considered multilevel image thresholding method is assessed on five test images. The experimental results demonstrate the successful utilization of the improved particle swarm optimization algorithm for determining image thresholds across different images. This algorithm is shown to enhance the multilevel image thresholding performance over the standard particle swarm optimization algorithm.