Jurnal Ilmu Komputer dan Informasi
Vol 6, No 1 (2013): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)

OPTIMUM MULTILEVEL THRESHOLDING HYBRID GA-PSO BY ALGORITHM

dwi taufik hidayat (Unknown)
Isnan . (Unknown)
Muhammad Ali Fauzi (Unknown)



Article Info

Publish Date
21 Oct 2013

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.

Copyrights © 2013






Journal Info

Abbrev

JIKI

Publisher

Subject

Computer Science & IT

Description

Jurnal Ilmu Komputer dan Informasi is a scientific journal in computer science and information containing the scientific literature on studies of pure and applied research in computer science and information and public review of the development of theory, method and applied sciences related to the ...