Facebook pixel tracking

The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

Contact Info
Email info@thesai.org
Website thesai.org
Follow Us
Contact Info
Email info@thesai.org
Follow Us
Research Article | Open Access |

Image Edge Detection based on ACO-PSO Algorithm

Author 1: Chen Tao Author 2: Sun Xiankun Author 3: Han Hua Author 4: You Xiaoming
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 6, No. 7 · Published 2015 · Cited by 9

DOI: https://doi.org/10.14569/IJACSA.2015.060708

Download PDF Cite Call for Papers

Abstract

This survey focuses on the problem of parameters selection in image edge detection by ant colony optimization (ACO) algorithm. By introducing particle swarm optimization (PSO) algorithm to optimize parameters in ACO algorithm, the fitness function based on connectivity of image edge is proposed to evaluate the quality of parameters in ACO algorithm. And the ACO-PSO algorithm is applied to image edge detection. The simulation results show that the parameters have been optimized and the proposed ACO-PSO algorithm presents better edges than traditional methods.

Keywords

Image edge detection ant colony optimization particle swarm optimization parameter optimization edge quality evaluation

How to Cite this Article

Tao, C., Xiankun, S., Hua, H., & Xiaoming, Y. (2015). Image Edge Detection based on ACO-PSO Algorithm. International Journal of Advanced Computer Science and Applications, 6(7). https://doi.org/10.14569/IJACSA.2015.060708

Tao, Chen, et al.. "Image Edge Detection based on ACO-PSO Algorithm." International Journal of Advanced Computer Science and Applications, vol. 6, no. 7, 2015, https://doi.org/10.14569/IJACSA.2015.060708.

@article{Tao2015,
  title     = {Image Edge Detection based on ACO-PSO Algorithm},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {6},
  number    = {7},
  year      = {2015},
  publisher = {The Science and Information Organization},
  author    = {Chen Tao and Sun Xiankun and Han Hua and You Xiaoming},
  doi       = {10.14569/IJACSA.2015.060708},
  url       = {https://doi.org/10.14569/IJACSA.2015.060708}
}

Open Access — licensed under a Creative Commons Attribution 4.0 International License. Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.

Back to Issue
IJACSA Journal Cover

IJACSA