Instruments and Systems: Monitoring, Control, and Diagnostics Annotation << Back Parallel Fuzzy C-Means Method for Image Segmentation P.I. KARASEV, YU.YU. GROMOV, I.A. METELEV, A.V. RYAZANTSEV This paper proposes a Parallel Fuzzy C-means (FCM) method for image segmentation. The parallel FCM method requires large computational costs and imposes signifi cant memory requirements. For many applications such as medical image segmentation and geographic image analysis that deal with large-size images, sequential FCM is very slow. In our Parallel FCM method, separating computations between processors and minimizing the need for access to secondary data storage increases the performance and effi ciency of the image segmentation task compared to the sequential method. Keywords: clustering by FCM method, image segmentation. DOI: 10.25791/pribor.12.2023.1461 Pp. 26-32.