A new technique for multilevel color image thresholding based on modified fuzzy entropy and Lévy flight firefly algorithm

•In this paper, a modified fuzzy entropy function is proposed using Lévy flight guided firefly algorithm.•Modified fuzzy entropy function is the difference of adjacent entropies.•In this approach, most widely used meta-heuristic techniques algorithms are exploited.•The experimental results reveal be...

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Bibliographic Details
Published in:Computers & electrical engineering 2018-08, Vol.70, p.476-495
Main Authors: Pare, S., Bhandari, A.K., Kumar, A., Singh, G.K.
Format: Article
Language:English
Subjects:
Algorithms
Color image segmentation
Color imagery
Comparative studies
Computer simulation
Entropy
Fitness
Fuzzy logic
Heuristic methods
Histograms
Image retrieval
Image segmentation
Lévy flight guided firefly algorithm
Modified fuzzy entropy
Multi-level thresholding
Satellite imagery
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Summary:•In this paper, a modified fuzzy entropy function is proposed using Lévy flight guided firefly algorithm.•Modified fuzzy entropy function is the difference of adjacent entropies.•In this approach, most widely used meta-heuristic techniques algorithms are exploited.•The experimental results reveal better performance of the proposed approach over other methods.•The validity of the proposed technique is reported both qualitatively and quantitatively. In this paper, a modified fuzzy entropy (MFE) function is proposed to perform the multilevel thresholding of color images at different segmentation levels using Lévy flight guided firefly algorithm (LFA). Modified fuzzy entropy function is the difference of adjacent entropies. Therefore, minimizing the fitness function will provide thresholding levels such that all the regions have almost equal entropies. LFA algorithm improves the search performance and gains optimal threshold values for an efficient segmentation of colored images and satellite images. A comparative study of different nature inspired algorithms using MFE as an objective function presented. The study proves that the proposed MFE-LFA algorithm exhibits better performance in terms of different fidelity parameters and computation time. In addition, the proposed method is also compared with the most widely used Kapur's entropy based segmentation approaches, where the simulation results show the proposed methodology as the most efficient and effective algorithm. [Display omitted]
ISSN:0045-7906
1879-0755
DOI:10.1016/j.compeleceng.2017.08.008