Year: 2025
Type: article
Abstract: This paper introduces an image segmentation framework using Interval-Valued Double Refined Triangular Neutrosophic Numbers to better handle uncertainty and imprecision in image data. The proposed model extends classical neutrosophic theory by incorporating interval-valued membership functions and double refinement strategies to handle higher degrees of uncertainty, indeterminacy, and inconsistency in image processing. An algorithm is developed for segmentation of the images and implemented using MATLAB and the effectiveness of the proposed algorithm is confirmed using the appropriate metrics.
Author: Gokilamani R
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409808774