An overview of Cuckoo Optimization Algorithm based Image Processing | ||
| AL-Rafidain Journal of Computer Sciences and Mathematics | ||
| Article 4, Volume 16, Issue 1, June 2022, Pages 31-36 PDF (729.93 K) | ||
| Document Type: Research Paper | ||
| DOI: 10.33899/csmj.2022.174393 | ||
| Author | ||
| Baydaa sulaiman* | ||
| Software Department, College of Computer science and Mathematics, University of Mosul, Mosul, Iraq | ||
| Abstract | ||
| The Cuckoo Search (CS) algorithm is an effective swarm intelligence optimization algorithm whose important developments were presented by Yang and Deb in 2009. The CS algorithm has been used in many applications to solve optimization problems. This paper describes an overview of the applications of CS in the scope of image processing to solve optimization problems for the image during the years 2015-2021. The main categories reviewed that used CS in the field of image processing are: image segmentation, image optimization, image noise removal, image classification, feature extraction in images, image clustering and edge detection. The aim of this paper is to provide an overview and summarize the literature review of applying CS algorithm in these categories in order to extract which categories that applied this algorithm more than others. From this review we conclude that CS was mostly applied in the image segmentation category to optimize the threshold search. | ||
| Keywords | ||
| Cuckoo Search Algorithm; swarm intelligence; Image Processing, Image segmentation | ||
|
Statistics Article View: 230 PDF Download: 236 |
||