Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
