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Improved Bat Algorithm Applied to Multilevel Image Thresholding
Joint Authors
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-03
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Multilevel image thresholding is a very important image processing technique that is used as a basis for image segmentation and further higher level processing.
However, the required computational time for exhaustive search grows exponentially with the number of desired thresholds.
Swarm intelligence metaheuristics are well known as successful and efficient optimization methods for intractable problems.
In this paper, we adjusted one of the latest swarm intelligence algorithms, the bat algorithm, for the multilevel image thresholding problem.
The results of testing on standard benchmark images show that the bat algorithm is comparable with other state-of-the-art algorithms.
We improved standard bat algorithm, where our modifications add some elements from the differential evolution and from the artificial bee colony algorithm.
Our new proposed improved bat algorithm proved to be better than five other state-of-the-art algorithms, improving quality of results in all cases and significantly improving convergence speed.
American Psychological Association (APA)
Alihodzic, Adis& Tuba, Milan. 2014. Improved Bat Algorithm Applied to Multilevel Image Thresholding. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-16.
https://search.emarefa.net/detail/BIM-1048603
Modern Language Association (MLA)
Alihodzic, Adis& Tuba, Milan. Improved Bat Algorithm Applied to Multilevel Image Thresholding. The Scientific World Journal No. 2014 (2014), pp.1-16.
https://search.emarefa.net/detail/BIM-1048603
American Medical Association (AMA)
Alihodzic, Adis& Tuba, Milan. Improved Bat Algorithm Applied to Multilevel Image Thresholding. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-16.
https://search.emarefa.net/detail/BIM-1048603
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1048603