Fuzzy Rule-Based Image Segmentation technique for rock thin section images

Image segmentation is a process of partitioning the images into meaningful regions that are ready to analyze. Segmentation of rock thin section images is not trivial task due to the unpredictable structures and features of minerals. In this paper, we propose Fuzzy Rule-Based Image Segmentation technique to segment rock thin section images. Proposed technique uses RGB images of rock thin sections as input and gives segmented into minerals images as output. In order to show an advantage of proposed technique the rock thin section images were also segmented by known Fuzzy C-Means technique. Both techniques were applied to many different rock thin section images. The obtained results of proposed Fuzzy Rule-Based Image Segmentation and Fuzzy C-Means techniques were compared. Implementation results showed that proposed image segmentation technique has better accuracy than known ones.