Instruments and Systems: Monitoring, Control, and Diagnostics Annotation << Back Modified Image Segmentation Method for Use in Decision Support Systems YU.YU. GROMOV, P.I. KARASEV, O.G. IVANOVA, SARI FARAH ABBAS To preserve more image detail and improve its robustness to noise during image segmentation, an improved Fuzzy C-Means (FCM) method is presented for image segmentation by incorporating local spatial information and grayscale level information. The modified membership function and the clustering center function are more mathematically justified than the FCM functions, so the iterative sequence can converge to the local minimum value of the improved objective function. The new fuzzy factor gives the method a new balance between noise immunity and detail retention efficiency. The revised flow method has greatly accelerated the processing procedure. The effectiveness of the proposed method is shown using experiments on artificial and real images. Keywords: clustering, image segmentation, fuzzy C-means, local minimum value, data gray level information. DOI: 10.25791/pribor.8.2021.1285 Pp. 38-43.