OPTIMUM MULTILEVEL THRESHOLDING HYBRID GA-PSO BY ALGORITHM
Abstract: The conventional
multilevel thresholding methods are efficient for bi-level thresholding.
However, these methods are computationally very expensive for use in multilevel
thresholding because the search of optimum threshold do in depth to optimize
the objective function. To overcome these drawbacks, a hybrid method of Genetic
Algorithm (GA) and Particle Swarm Optimization (PSO), called GA-PSO, based
multilevel thresholding is presented in this paper. GA-PSO algorithm is used to
find the optimal threshold value to maximize the objective function of the Otsu
method. GA-PSO method proposed has been tested on five standard test images and
compared with particle swarm optimization algorithm (PSO) and genetic algorithm
(GA). The results showed the effectiveness in the search for optimal multilevel
threshold of the proposed algorithm.
Keywords: multilevel
thresholding; image segmentation; histogram; genetic algorithm; particle swarm
optimization; GA-PSO; otsu function
Author: dwi taufik hidayat,
Isnan ., Muhammad Ali Fauzi
Journal Code: jptkomputergg130004
