skip to main content
10.1145/3377929.3389909acmconferencesArticle/Chapter ViewAbstractPublication PagesgeccoConference Proceedingsconference-collections
poster

Effective image clustering using self-organizing migrating algorithm

Published: 08 July 2020 Publication History

Abstract

Image segmentation is an important task in computer vision. Clustering is a common image segmentation approach which divides an image into homogeneous regions, but conventional clustering algorithms such as k-means have a tendency of getting stuck in local optima. In this paper, we propose a novel clustering algorithm based on the Self-Organizing Migrating Algorithm (SOMA). In particular, we adopt SOMA Team To Team Adaptive (SOMA T3A), a recent variant of SOMA, to image clustering. Experimental results on a set of benchmark images show excellent image clustering performance, also in comparison to other state-of-the-art metaheuristics.

References

[1]
S. Das and A. Konar. 2009. Automatic image pixel clustering with an improved differential evolution. Applied Soft Computing 9, 1 (2009), 226--236.
[2]
D. Davendra and I. Zelinka (Eds.). 2016. Self-Organizing Migrating Algorithm - Methodology and Implementation. Springer.
[3]
Q. B. Diep. 2019. Self-organizing migrating algorithm Team To Team adaptive - SOMA T3A. In IEEE Congress on Evolutionary Computation. 1182--1187.
[4]
Z. W. Geem, J. H. Kim, and G. V. Loganathan. 2001. A new heuristic optimization algorithm: harmony search. Simulation 76, 2 (2001), 60--68.
[5]
D. Karaboga and B. Basturk. 2007. A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. Journal of Global Optimization 39, 3 (2007), 459--471.
[6]
W. Kwedlo. 2011. A clustering method combining differential evolution with the k-means algorithm. Pattern Recognition Letters 32, 12 (2011), 1613--1621.
[7]
D. Martin, C. Fowlkes, D. Tal, and J. Malik. 2001. A Database of Human Segmented Natural Images and its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics. In 8th International Conference on Computer Vision, Vol. 2. 416--423.
[8]
M. G. Omran, A. P. Engelbrecht, and A. Salman. 2004. Image classification using particle swarm optimization. In Recent Advances in Simulated Evolution and Learning. World Scientific, 347--365.
[9]
C. Ozturk, E. Hancer, and D. Karaboga. 2015. Improved clustering criterion for image clustering with artificial bee colony algorithm. Pattern Analysis and Applications 18, 3 (2015), 587--599.
[10]
K. Price, N. Awad, M. Ali, and P. Suganthan. 2018. Problem definitions and evaluation criteria for the 100-digit challenge special session and competition on single objective numerical optimization. Technical Report. Nanyang Technological University.
[11]
Y. Shi and R. Eberhart. 1998. A modified particle swarm optimizer. In IEEE International Conference on Evolutionary Computation. 69--73.
[12]
R. Storn and K. Price. 1997. Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization 11, 4 (1997), 341--359.
[13]
L. Wang, Y. Yufeng, and J. Liu. 2016. Clustering with a Novel Global Harmony Search Algorithm for Image Segmentation. International Journal of Hybrid Information Technology 9, 2 (2016), 183--194.
[14]
D. Whitley. 1994. A genetic algorithm tutorial. Statistics and Computing 4, 2 (1994), 65--85.
[15]
I. Zelinka and J. Lampinen. 2000. SOMA - self-organizing migrating algorithm. In 6th International Conference on Soft Computing.

Cited By

View all
  • (2022)Self-organizing migrating algorithm: review, improvements and comparisonArtificial Intelligence Review10.1007/s10462-022-10167-856:1(101-172)Online publication date: 4-Apr-2022
  • (2021)A population-based automatic clustering algorithm for image segmentationProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3449726.3463148(1931-1936)Online publication date: 7-Jul-2021
  • (2020)One-array Differential Evolution Algorithm with a Novel Replacement Strategy for Numerical Optimization2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)10.1109/SMC42975.2020.9283154(2514-2519)Online publication date: 11-Oct-2020

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion
July 2020
1982 pages
ISBN:9781450371278
DOI:10.1145/3377929
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 July 2020

Check for updates

Author Tags

  1. SOMA
  2. image clustering
  3. image segmentation
  4. optimisation

Qualifiers

  • Poster

Funding Sources

Conference

GECCO '20
Sponsor:

Acceptance Rates

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)6
  • Downloads (Last 6 weeks)1
Reflects downloads up to 20 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2022)Self-organizing migrating algorithm: review, improvements and comparisonArtificial Intelligence Review10.1007/s10462-022-10167-856:1(101-172)Online publication date: 4-Apr-2022
  • (2021)A population-based automatic clustering algorithm for image segmentationProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3449726.3463148(1931-1936)Online publication date: 7-Jul-2021
  • (2020)One-array Differential Evolution Algorithm with a Novel Replacement Strategy for Numerical Optimization2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)10.1109/SMC42975.2020.9283154(2514-2519)Online publication date: 11-Oct-2020

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media