Sonar image segmentation on Fuzzy C-Mean using local texture feature

摘要

This paper proposes an improved Fuzzy C-Mean (FMC) algorithm for scan sonar image segmentation. Taking care of the characteristics of sonar images which are poor contrast, low resolution and strong noise, we propose to use local texture features and original image to calculate the distance of the pixels and the center of clusters .First, we use the Gauss-Markov Random Field (GMRF) model to extract Local texture features. Then, we form a new FMC clustering criterion to complete the sonar image segmentation. Experimental data show that the segmentation results of our clustering method are superior to the standard FMC and.