Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
One of the population-based heuristic global search algorithms is the Particle Swarm Optimization (PSO) algorithm that is motivated through patterns of social behavior of organisms which live and interact within large groups. The PSO is depended on researches on swarms such as fish schooling and bird flocking Quantum Particle Swarm (Q-PSO) algorithm based on quantum individual, the theory of quantum used the change the adapting mode of the particles. In this study, Q-PSO algorithm was used in order to enhance the speed of search and the convergence precision and guarantee the effectiveness and simplification. It is simpler and more powerful than the algorithms available. The simulation and its application in the feature extraction prove its high efficiency.
How to cite this article:
Seba Aziz Sahy. Image Feature Extraction using Quantum-PSO and Chaotic Map.
DOI: https://doi.org/10.36478/jeasci.2019.2352.2359
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2019.2352.2359