Automatic Detection of Galaxy Type From Datasets of Galaxies Image Based on Image Retrieval Approach

Abstract This paper presents a new approach for the automatic detection of galaxy morphology from datasets based on an image-retrieval approach. Currently, there are several classification methods proposed to detect galaxy types within an image. However, in some situations, the aim is not only to de...

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Autores principales:	Mohamed Abd El Aziz, I. M. Selim, Shengwu Xiong
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f3bd9ec0d5ec46ad8a8e69c604451e14
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spelling	oai:doaj.org-article:f3bd9ec0d5ec46ad8a8e69c604451e142021-12-02T16:06:59ZAutomatic Detection of Galaxy Type From Datasets of Galaxies Image Based on Image Retrieval Approach10.1038/s41598-017-04605-92045-2322https://doaj.org/article/f3bd9ec0d5ec46ad8a8e69c604451e142017-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-04605-9https://doaj.org/toc/2045-2322Abstract This paper presents a new approach for the automatic detection of galaxy morphology from datasets based on an image-retrieval approach. Currently, there are several classification methods proposed to detect galaxy types within an image. However, in some situations, the aim is not only to determine the type of galaxy within the queried image, but also to determine the most similar images for query image. Therefore, this paper proposes an image-retrieval method to detect the type of galaxies within an image and return with the most similar image. The proposed method consists of two stages, in the first stage, a set of features is extracted based on shape, color and texture descriptors, then a binary sine cosine algorithm selects the most relevant features. In the second stage, the similarity between the features of the queried galaxy image and the features of other galaxy images is computed. Our experiments were performed using the EFIGI catalogue, which contains about 5000 galaxies images with different types (edge-on spiral, spiral, elliptical and irregular). We demonstrate that our proposed approach has better performance compared with the particle swarm optimization (PSO) and genetic algorithm (GA) methods.Mohamed Abd El AzizI. M. SelimShengwu XiongNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-9 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Mohamed Abd El Aziz I. M. Selim Shengwu Xiong Automatic Detection of Galaxy Type From Datasets of Galaxies Image Based on Image Retrieval Approach
description	Abstract This paper presents a new approach for the automatic detection of galaxy morphology from datasets based on an image-retrieval approach. Currently, there are several classification methods proposed to detect galaxy types within an image. However, in some situations, the aim is not only to determine the type of galaxy within the queried image, but also to determine the most similar images for query image. Therefore, this paper proposes an image-retrieval method to detect the type of galaxies within an image and return with the most similar image. The proposed method consists of two stages, in the first stage, a set of features is extracted based on shape, color and texture descriptors, then a binary sine cosine algorithm selects the most relevant features. In the second stage, the similarity between the features of the queried galaxy image and the features of other galaxy images is computed. Our experiments were performed using the EFIGI catalogue, which contains about 5000 galaxies images with different types (edge-on spiral, spiral, elliptical and irregular). We demonstrate that our proposed approach has better performance compared with the particle swarm optimization (PSO) and genetic algorithm (GA) methods.
format	article
author	Mohamed Abd El Aziz I. M. Selim Shengwu Xiong
author_facet	Mohamed Abd El Aziz I. M. Selim Shengwu Xiong
author_sort	Mohamed Abd El Aziz
title	Automatic Detection of Galaxy Type From Datasets of Galaxies Image Based on Image Retrieval Approach
title_short	Automatic Detection of Galaxy Type From Datasets of Galaxies Image Based on Image Retrieval Approach
title_full	Automatic Detection of Galaxy Type From Datasets of Galaxies Image Based on Image Retrieval Approach
title_fullStr	Automatic Detection of Galaxy Type From Datasets of Galaxies Image Based on Image Retrieval Approach
title_full_unstemmed	Automatic Detection of Galaxy Type From Datasets of Galaxies Image Based on Image Retrieval Approach
title_sort	automatic detection of galaxy type from datasets of galaxies image based on image retrieval approach
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/f3bd9ec0d5ec46ad8a8e69c604451e14
work_keys_str_mv	AT mohamedabdelaziz automaticdetectionofgalaxytypefromdatasetsofgalaxiesimagebasedonimageretrievalapproach AT imselim automaticdetectionofgalaxytypefromdatasetsofgalaxiesimagebasedonimageretrievalapproach AT shengwuxiong automaticdetectionofgalaxytypefromdatasetsofgalaxiesimagebasedonimageretrievalapproach
_version_	1718384815329247232

Automatic Detection of Galaxy Type From Datasets of Galaxies Image Based on Image Retrieval Approach

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