Abstract: The majority of manufacturers demand increasingly powerful vision systems for quality control. To have good outcomes, the installation requires an effort in the vision system tuning, for both hardware and software. As time and accuracy are important, actors are oriented to automate parameter’s adjustment optimization at least in image processing. This paper suggests an approach based on discrete particle swarm optimization (DPSO) that automates software setting and provides optimal parameters for industrial vision applications. A novel update functions for our DPSO definition are suggested. The proposed method is applied on some real examples of quality control to validate its feasibility and efficiency, which shows that the new DPSO model furnishes promising results.

Benchikhi Loubna, Sadgal Mohamed, Elfazziki Abdelaziz and Mansouri Fatimaezzahra, “A Discrete Particle Swarm Optimization to Estimate Parameters in Vision Tasks” International Journal of Advanced Computer Science and Applications(IJACSA), 7(1), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070128

@article{Loubna2016,
title = {A Discrete Particle Swarm Optimization to Estimate Parameters in Vision Tasks},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070128},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070128},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {1},
author = {Benchikhi Loubna and Sadgal Mohamed and Elfazziki Abdelaziz and Mansouri Fatimaezzahra}
}