Multi-class Image Segmentation Using Theory of Weak String Energy and Fuzzy Set

Abstract

Segmentation of a multi-class image is a major challenging work in image processing. The challenge arises as the uncertainties occur in the segmentation process. Here we present a novel method based on the concept of weak string energy to manage the uncertainties in the segmentation process. The concept of the weak string is utilized to find the location of the boundaries accurately among the segments. The segments of an image are generated based on the energy function in the fuzzy set domain in the proposed method. The accurate segments are generated when the function attains its minimum value. The segments are generated from an image without any prior knowledge about the total count of segments. The performance of the method is verified experimentally using different datasets and it is found to be quite satisfactory compared to the state-of-the-art methods.