Akademik Veri Yönetim Sistemi
2025 33rd Signal Processing and Communications Applications Conference (SIU), İstanbul, Türkiye, 25 - 28 Haziran 2025, ss.1-4, (Tam Metin Bildiri)
Image segmentation plays a crucial role in the field of image processing. Fuzzy c-means algorithm is widely used in image segmentation because it is an easy and effective method. However, this method has certain limitations, including dependence on initial values, susceptibility to local optima, and difficulty in differentiating objects with similar color intensities. Therefore, in this study, a hybrid meta-heuristic method is proposed by combining the Sine Cosine Algorithm and Chernobyl Disaster Optimization, and it is used to segment X-Ray images of patients with COVID-19 based on the objective function of fuzzy c-means. It is compared with well-known algorithms such as Light Spectrum Optimization, Remora Optimization Algorithm, and Bat Algorithm according to different performance metrics to prove the performance of the proposed method. The obtained results show that the proposed fuzzy hybrid method is more effective and superior than the other algorithms.