Original paper
Shannon and Fuzzy entropy based evolutionary image thresholding for image segmentation
Abstract
Image segmentation is a very important and pre-processing step in image analysis. The conventional multilevel thresholding methods are efficient for bi-level thresholding because of its simplicity, robustness, less convergence time and accuracy. However, a mass of computational cost is needed and efficiency is broken down as an exhaustive search is utilized for finding the optimal thresholds, which results in application of evolutionary...
Paper Details
Title
Shannon and Fuzzy entropy based evolutionary image thresholding for image segmentation
Published Date
Jun 20, 2017
Volume
57
Issue
3
Pages
1643 - 1655