2019
DOI: 10.1109/access.2019.2959325
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A Multilevel Image Thresholding Based on Hybrid Salp Swarm Algorithm and Fuzzy Entropy

Abstract: The image segmentation techniques based on multi-level threshold value received lot of attention in recent years. It is because they can be used as a pre-processing step in complex image processing applications. The main problem in identifying the suitable threshold values occurs when classical image segmentation methods are employed. The swarm intelligence (SI) technique is used to improve multi-level threshold image (MTI) segmentation performance. SI technique simulates the social behaviors of swarm ecosyste… Show more

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Cited by 31 publications
(24 citation statements)
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“…Moreover, SSA is also an optimization algorithm proposed by Mirjalili et al [48] inspired by the behavior of salp chains. In recent years, the SSA was utilized to solve different optimization problems, such as feature selection [49,50], data classification [51], image segmentation [52], and others [53,54].…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, SSA is also an optimization algorithm proposed by Mirjalili et al [48] inspired by the behavior of salp chains. In recent years, the SSA was utilized to solve different optimization problems, such as feature selection [49,50], data classification [51], image segmentation [52], and others [53,54].…”
Section: Introductionmentioning
confidence: 99%
“…The second step was performed based on the line symmetry to directly obtain the upper-right and the bottom-left quarters of the elements according to the mapping functions in (11), (12), as shown at the bottom of the next page. The last step was based on the point symmetry, namely to directly obtain the bottom-right quarters of the elements by using (13). The number of basic computations was R 2 × C 2 × (R × C − 1) with this improved method (e.g., 0.3240×10 11 for a 600 × 600 image).…”
Section: Symmetry-based Methods For Efficiently Constructing a Loomentioning
confidence: 99%
“…efficient method for this assessment is to employ information entropy (IE, also called Shannon entropy) [5]- [9], which is an information-theoretic metric that quantifies the information content of a dataset [10]. This method has been extensively used because of its theoretical elegance and practical simplicity, which helped create numerous image processing algorithms [11]- [13].…”
Section: Introductionmentioning
confidence: 99%
“…The hybrid method is based on the gravitational search algorithm and genetic algorithm. In Reference [ 27 ], a hybrid multi-level thresholding method is proposed based on an improved salp swarm optimizer and Fuzzy entropy. The MFO is used to overcome the limitation of the salp swarm algorithm.…”
Section: Introductionmentioning
confidence: 99%
“…However, in such hybrid methods, one MH algorithm is needed to improve the local search for the other MH algorithm, such as, in Reference [ 27 ], the MFO is used as a local search for SSA. These hybrid MH methods can solve optimization problems efficiently.…”
Section: Introductionmentioning
confidence: 99%