Next Article in Journal / Special Issue
Image Encryption Based on Pixel-Level Diffusion with Dynamic Filtering and DNA-Level Permutation with 3D Latin Cubes
Previous Article in Journal
Intra- and Inter-Modular Connectivity Alterations in the Brain Structural Network of Spinocerebellar Ataxia Type 3
Previous Article in Special Issue
Primality, Fractality, and Image Analysis
Article Menu
Issue 3 (March) cover image

Export Article

Open AccessArticle
Entropy 2019, 21(3), 318; https://doi.org/10.3390/e21030318

Kapur’s Entropy for Color Image Segmentation Based on a Hybrid Whale Optimization Algorithm

College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China
*
Author to whom correspondence should be addressed.
Received: 14 March 2019 / Accepted: 21 March 2019 / Published: 23 March 2019
(This article belongs to the Special Issue Entropy in Image Analysis)
  |  
PDF [96400 KB, uploaded 23 March 2019]
  |  

Abstract

In this paper, a new hybrid whale optimization algorithm (WOA) called WOA-DE is proposed to better balance the exploitation and exploration phases of optimization. Differential evolution (DE) is adopted as a local search strategy with the purpose of enhancing exploitation capability. The WOA-DE algorithm is then utilized to solve the problem of multilevel color image segmentation that can be considered as a challenging optimization task. Kapur’s entropy is used to obtain an efficient image segmentation method. In order to evaluate the performance of proposed algorithm, different images are selected for experiments, including natural images, satellite images and magnetic resonance (MR) images. The experimental results are compared with state-of-the-art meta-heuristic algorithms as well as conventional approaches. Several performance measures have been used such as average fitness values, standard deviation (STD), peak signal to noise ratio (PSNR), structural similarity index (SSIM), feature similarity index (FSIM), Wilcoxon’s rank sum test, and Friedman test. The experimental results indicate that the WOA-DE algorithm is superior to the other meta-heuristic algorithms. In addition, to show the effectiveness of the proposed technique, the Otsu method is used for comparison. View Full-Text
Keywords: Kapur’s entropy; color image segmentation; whale optimization algorithm; differential evolution; hybrid algorithm; Otsu method Kapur’s entropy; color image segmentation; whale optimization algorithm; differential evolution; hybrid algorithm; Otsu method
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Lang, C.; Jia, H. Kapur’s Entropy for Color Image Segmentation Based on a Hybrid Whale Optimization Algorithm. Entropy 2019, 21, 318.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top