Multi-objective whale optimization algorithm for content-based image retrieval

In the recent years, there are massive digital images collections in many fields of our life, which led the technology to find methods to search and retrieve these images efficiently. The content-based is one of the popular methods used to retrieve images, which depends on the color, texture and sha...

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Vydáno v:Multimedia tools and applications Ročník 77; číslo 19; s. 26135 - 26172
Hlavní autoři: Aziz, Mohamed Abd El, Ewees, Ahmed A., Hassanien, Aboul Ella
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.10.2018
Springer Nature B.V
Témata:
Classification
Complexity
Computer Communication Networks
Computer Science
Data Structures and Information Theory
Digital imaging
Feature extraction
Image classification
Image management
Image retrieval
Multimedia Information Systems
Multiple objective analysis
Optimization
Optimization algorithms
Sorting algorithms
Special Purpose and Application-Based Systems
Content based image retrieval
Feature selection
Multi-objective optimization
Whale optimization algorithm
Non-dominated sorting
ISSN:1380-7501, 1573-7721
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Shrnutí:In the recent years, there are massive digital images collections in many fields of our life, which led the technology to find methods to search and retrieve these images efficiently. The content-based is one of the popular methods used to retrieve images, which depends on the color, texture and shape descriptors to extract features from images. However, the performance of the content-based image retrieval methods depends on the size of features that are extracted from images and the classification accuracy. Therefore, this problem is considered as a multi-objective and there are several methods that used to manipulate it such as NSGA-II and NSMOPSO. However, these methods have drawbacks such as their time and space complexity are large since they used traditional non-dominated sorting methods. In this paper, a new non-dominated sorting based on multi-objective whale optimization algorithm is proposed for content-based image retrieval (NSMOWOA). The proposed method avoids the drawbacks in other non-dominated sorting multi-objective methods that have been used for content-based image retrieval through reducing the space and time complexity. The results of the NSMOWOA showed a good performance in content-based image retrieval problem in terms of recall and precision.
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ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-018-5840-9