OPTIMUM MULTILEVEL THRESHOLDING HYBRID GA-PSO BY ALGORITHM

Authors

  • dwi taufik hidayat
  • Isnan .
  • Muhammad Ali Fauzi

DOI:

https://doi.org/10.21609/jiki.v6i1.210

Keywords:

multilevel thresholding, image segmentation, histogram, genetic algorithm, particle swarm optimization, GA-PSO, otsu function

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.

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Published

2013-10-21

How to Cite

hidayat, dwi taufik, ., I., & Fauzi, M. A. (2013). OPTIMUM MULTILEVEL THRESHOLDING HYBRID GA-PSO BY ALGORITHM. Jurnal Ilmu Komputer Dan Informasi, 6(1), 1–5. https://doi.org/10.21609/jiki.v6i1.210

Issue

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

Section

Articles

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