OPTIMUM MULTILEVEL THRESHOLDING HYBRID GA-PSO BY ALGORITHM

dwi taufik hidayat, Isnan ., Muhammad Ali Fauzi

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

Full Text:

PDF


DOI: http://dx.doi.org/10.21609/jiki.v6i1.210

Refbacks

  • There are currently no refbacks.


Copyright © Jurnal Ilmu Komputer dan Informasi. Faculty of Computer Science Universitas Indonesia.

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

View JIKI Statistic