Neutrosophic Features for Image Retrieval

Authors

  • Ahmed A.Salama Port Said University , Faculty of Science, Department of Mathematics and Computer Science
  • Mohamed Eisa Port Said University , Higher Institute of Management and Computer, Computer Science Department
  • A.E. Fawzy Port Said University , Higher Institute of Management and Computer, Computer Science Department
  • Hewayda ElGhawalby Port Said University , Faculty of Engineering , Physics and Engineering Mathematics Department

Keywords:

Content-Based Image Retrieval (CBIR), Textbased Image Retrieval (TBIR), Neutrosophic Domain, Neutrosophic Entropy, Neutrosophic Contrast, Neutrosophic Energy, Neutrosophic Homogeneity

Abstract

Abstract The goal of an Image Retrieval System is to retrieve images that are relevant to the user's request from a large image collection. In this paper, we present texture features for images embedded in the neutrosophic domain. The aim is to extract a set of features to represent the content of each image in the training database to be used for the purpose of retrieving images from the database similar to the image under consideration. with the rapid increase of using digital images databases on the internet. Used for retrieving, managing and navigating large digital images databases, the CBIR techniques index the images by their own visual content, such as color and texture, instead of annotated the image manually by text-based key words [11, 16, 22, 23, 36]. The Neutrosophic logic which proposed by Samarandache in [40] is a generalization of fuzzy sets which introduced by Zada at 1965 [45], The fundamental concepts of neutrosophic set, introduced by Samarandache in [41, 42] and Salama etl in [1, 14, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35].

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Author Biographies

  • Ahmed A.Salama, Port Said University , Faculty of Science, Department of Mathematics and Computer Science

    Abstract The goal of an Image Retrieval System is to retrieve images that are relevant to the user's request from a large image collection. In this paper, we present texture features for images embedded in the neutrosophic domain. The aim is to extract a set of features to represent the content of each image in the training database to be used for the purpose of retrieving images from the database similar to the image under consideration. with the rapid increase of using digital images databases on the internet. Used for retrieving, managing and navigating large digital images databases, the CBIR techniques index the images by their own visual content, such as color and texture, instead of annotated the image manually by text-based key words [11, 16, 22, 23, 36]. The Neutrosophic logic which proposed by Samarandache in [40] is a generalization of fuzzy sets which introduced by Zada at 1965 [45], The fundamental concepts of neutrosophic set, introduced by Samarandache in [41, 42] and Salama etl in [1, 14, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35].

  • Mohamed Eisa, Port Said University , Higher Institute of Management and Computer, Computer Science Department

    Abstract The goal of an Image Retrieval System is to retrieve images that are relevant to the user's request from a large image collection. In this paper, we present texture features for images embedded in the neutrosophic domain. The aim is to extract a set of features to represent the content of each image in the training database to be used for the purpose of retrieving images from the database similar to the image under consideration. with the rapid increase of using digital images databases on the internet. Used for retrieving, managing and navigating large digital images databases, the CBIR techniques index the images by their own visual content, such as color and texture, instead of annotated the image manually by text-based key words [11, 16, 22, 23, 36]. The Neutrosophic logic which proposed by Samarandache in [40] is a generalization of fuzzy sets which introduced by Zada at 1965 [45], The fundamental concepts of neutrosophic set, introduced by Samarandache in [41, 42] and Salama etl in [1, 14, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35].

  • A.E. Fawzy, Port Said University , Higher Institute of Management and Computer, Computer Science Department

    Abstract The goal of an Image Retrieval System is to retrieve images that are relevant to the user's request from a large image collection. In this paper, we present texture features for images embedded in the neutrosophic domain. The aim is to extract a set of features to represent the content of each image in the training database to be used for the purpose of retrieving images from the database similar to the image under consideration. with the rapid increase of using digital images databases on the internet. Used for retrieving, managing and navigating large digital images databases, the CBIR techniques index the images by their own visual content, such as color and texture, instead of annotated the image manually by text-based key words [11, 16, 22, 23, 36]. The Neutrosophic logic which proposed by Samarandache in [40] is a generalization of fuzzy sets which introduced by Zada at 1965 [45], The fundamental concepts of neutrosophic set, introduced by Samarandache in [41, 42] and Salama etl in [1, 14, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35].

  • Hewayda ElGhawalby, Port Said University , Faculty of Engineering , Physics and Engineering Mathematics Department

    Abstract The goal of an Image Retrieval System is to retrieve images that are relevant to the user's request from a large image collection. In this paper, we present texture features for images embedded in the neutrosophic domain. The aim is to extract a set of features to represent the content of each image in the training database to be used for the purpose of retrieving images from the database similar to the image under consideration. with the rapid increase of using digital images databases on the internet. Used for retrieving, managing and navigating large digital images databases, the CBIR techniques index the images by their own visual content, such as color and texture, instead of annotated the image manually by text-based key words [11, 16, 22, 23, 36]. The Neutrosophic logic which proposed by Samarandache in [40] is a generalization of fuzzy sets which introduced by Zada at 1965 [45], The fundamental concepts of neutrosophic set, introduced by Samarandache in [41, 42] and Salama etl in [1, 14, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35].

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Published

2016-12-15

Issue

Vol. 13 (2016): Neutrosophic Sets and Systems

Section

SI#1,2024: Neutrosophical Advancements And Their Impact on Research

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

 Creative Commons Attribution (CC BY) license.

How to Cite

A.Salama, A., Eisa, M. ., Fawzy, A., & ElGhawalby, . H. . (2016). Neutrosophic Features for Image Retrieval . Neutrosophic Sets and Systems, 13, 56-61. http://fs.unm.edu/nss8/index.php/111/article/view/473

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