CFP last date
20 March 2024
Call for Paper
April Edition
IJCA solicits high quality original research papers for the upcoming April edition of the journal. The last date of research paper submission is 20 March 2024

Submit your paper
Know more
Reseach Article

Ant Based Swarm Computing for Image Classification - A Brief Survey

Published on November 2012 by Rebika Rai, Ratika Pradhan, M. K. Ghose
Computational Intelligence & Information Security
Foundation of Computer Science USA
CIIS - Number 1
November 2012
Authors: Rebika Rai, Ratika Pradhan, M. K. Ghose
fbf0b895-a706-4831-ad5e-76fe6a7e9619

Rebika Rai, Ratika Pradhan, M. K. Ghose . Ant Based Swarm Computing for Image Classification - A Brief Survey. Computational Intelligence & Information Security. CIIS, 1 (November 2012), 17-21.

@article{
author = { Rebika Rai, Ratika Pradhan, M. K. Ghose },
title = { Ant Based Swarm Computing for Image Classification - A Brief Survey },
journal = { Computational Intelligence & Information Security },
issue_date = { November 2012 },
volume = { CIIS },
number = { 1 },
month = { November },
year = { 2012 },
issn = 0975-8887,
pages = { 17-21 },
numpages = 5,
url = { /specialissues/ciis/number1/9413-1004/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Computational Intelligence & Information Security
%A Rebika Rai
%A Ratika Pradhan
%A M. K. Ghose
%T Ant Based Swarm Computing for Image Classification - A Brief Survey
%J Computational Intelligence & Information Security
%@ 0975-8887
%V CIIS
%N 1
%P 17-21
%D 2012
%I International Journal of Computer Applications
Abstract

The social insect metaphor for solving problems has become an emerging topic in the recent years. This approach emphasizes on direct or indirect interactions among simple agents. Swarm Intelligence is the collective behavior of decentralized [8], self-organized [4] system whereby the collective behavior of agent interacting locally with the environment causes coherent global pattern to emerge. Classification is a computational procedure that sorts the image into groups according to their similarities [5]. Images can be similar but to measure the similarity pixel-to-pixel comparison is made. Numerous methods for classification have been developed. Exploring new methods to increase classification accuracies have been a key topic. This paper explores the swarm computing methods called Ant Colony Optimization (ACO) to classify imagery.

References
  1. Ling Chen, Bolun Chen and Yixin Chen, 2011, "Image Feature Selection Based on Ant Colony Optimization", AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence, pp. 580-589.
  2. Simranjeet Kaur, Prateek Agarwal, Rajbir Singh Rana, 2011" Ant Colony Optimization: A Technique used for Image Processing, Dept. of CSE, Lovely Professional University, IJCST Vol. 2, Issue 2.
  3. Lintao Wen, Qian Yin, Ping Guo, 2009, "Ant Colony Optimization algorithm for feature selection and Classification of multispectral remote sensing image", 2nd International congress on Image and Signal Processing, CISP'09.
  4. Rebika Rai, Tejbanta Singh Chinghtam, M. K. Ghose, 2009, "Optimization of Autonomous Multi-Robot Path Planning & Navigation using Swarm Intelligence", In National Conference on LEAN Manufacturing Implementations : The future of Process Industries (LEMAN '2009)".
  5. Xiaoping Liu, Xia Li, Lin Liu, Jinqiang He and Bin Ai, 2008, "An Innovative method to classify Remote-Sensing Images using Ant colony Optimization", IEEE transactions on geoscience and remote sensing, vol. 46, no. 12.
  6. T. Piatrik and E. Izquierdo, 2008, "An Application of Ant Colony Optimization to Image Clustering," in Proc. K-Space Jamboree Workshop.
  7. S. N. Omkar, Manoj Kumar M, Dheevatsa Mudigere, Dipti Muley, 2007, "Urban Satellite Image Classification using Biologically Inspired Techniques", In: IEEE International Symposium on Industrial Electronics.
  8. H. Liu, F. Hussain, C. L. Tan, and M. Dash, 2002, "Discretization: An enabling technique," Data Mining Knowl. Discovery, vol. 6, no. 4, pp. 393–423.
  9. R. Eberhart, Y. Shi, and J. Kennedy, 2001, Swarm Intelligence. San Francisco, CA: Morgan Kaufmann.
  10. M. Dorigo and L. M. Gambardella, 1997, "Ant colony system: A cooperative learning approach to the traveling salesman problem," IEEE Trans. Evol. Comput. vol. 1, no. 1, pp. 53–66.
  11. H. Gutowitz, "Complexity-seeking ants", 1993, In Proc. of the Third European Conference on Artificial Life.
  12. M. Dorigo, 1992, "Optimization, learning and natural algorithms," Ph. D. dissertation, Dept. Electron. , Politecnico di Milano, Milan, Italy.
Index Terms

Computer Science
Information Sciences

Keywords

Ant Colony Optimization (aco) Artificial Intelligence (ai) Swarm Intelligence (si)