WSEAS Transactions on Signal Processing
Print ISSN: 1790-5052, E-ISSN: 2224-3488
Volume 19, 2023
Retinal Vessel Segmentation based on Hunger Games Search and Reptile Search Algorithms
Authors: ,
Abstract: Metaheuristic algorithms may provide effective performance in image processing due to their strengthened random search abilities. In most of these algorithms, the intelligent collective behavior of animal swarms or individual intelligent behaviors of each animal is simulated. In this work, two recently proposed metaheuristic algorithms of hunger games search (HGS) and reptile search (RSA) algorithms are improved as clustering-based and then applied to the clustering of retinal image pixels. A detailed performance comparison is realized between HGS and RSA algorithms in terms of convergence speed, sensitivity, specificity, accuracy, mean squared error, standard deviation, and CPU time. Although HGS and RSA algorithms produce similar results in terms of clustering performance, it is observed that the HGS algorithm presents relatively better performance than the RSA algorithm in terms of all performance metrics. The simulation results obtained prove that HGS and RSA algorithms can successfully be used in retinal vessel segmentation.
Search Articles
Keywords: Retinal vessel segmentation, Clustering, DRIVE database, Metaheuristic algorithms, Hunger Games search algorithm, Reptile search algorithm
Pages: 221-228
DOI: 10.37394/232014.2023.19.24