Zagazig University Digital Repository
Home
Thesis & Publications
All Contents
Publications
Thesis
Graduation Projects
Research Area
Research Area Reports
Search by Research Area
Universities Thesis
ACADEMIC Links
ACADEMIC RESEARCH
Zagazig University Authors
Africa Research Statistics
Google Scholar
Research Gate
Researcher ID
CrossRef
Classification of galaxy color images using quaternion polar complex exponential transform and binary Stochastic Fractal Search
Faculty
Science
Year:
2020
Type of Publication:
ZU Hosted
Pages:
Authors:
Mohamed El Sayed Ahmed Muhamed
Staff Zu Site
Abstract In Staff Site
Journal:
Astronomy and Computing ُElsevier
Volume:
Keywords :
Classification , galaxy color images using quaternion
Abstract:
Galaxies’ studies play an important role in the astronomic. Accurate classification of these galaxies enables scientists to understand the formation and evolution of the Universe. During the last decades, there have been several methods applied to classify the galaxy images. However, these methods encounter three big challenges. First, most existing methods converted the color images of galaxies into gray images which result in losing the essential color information. Second, the utilized feature selection methods, that used to remove the irrelevant features, may be stuck at the attractive local point. Third, using an irrelevant classifier could lead to decrease the classification accuracy. In this paper, a new algorithm is proposed to classify color images of galaxies. In this algorithm, highly accurate non-redundant color features are extracted from the color images of galaxies by using the quaternion polar complex exponential transform moments (QPCET). The quaternion representation deals with a color image in a holistic way which keeps the correlation between components and then successfully represents the color images. The QPCET moments are highly accurate, noise resistant, and numerically stable. Moreover, these moments are invariants with respect to rotation, scaling and translation (RST). These characteristics assure the excellency of the extracted color features. The Stochastic Fractal Search (SFS) has a very high ability to avoid the stuck at local point. Its binary version is utilized to select the most appropriate features which improve the classification process. The Extreme Machine learning (EML) is used to classify the color images of galaxies using the selected color features. Experiments are performed with the well-known datasets of galaxies (EFIGI catalog), where the proposed algorithm achieved high classification rate. The obtained results clearly show that the proposed method outperformed all existing galaxies classification methods.
Author Related Publications
Mohamed El Sayed Ahmed Muhamed, "A Grunwald–Letnikov based Manta ray foraging optimizer for global optimization and image segmentation", Elsevier, 2020
More
Mohamed El Sayed Ahmed Muhamed, "A novel hybrid gradient-based optimizer and grey wolf optimizer feature selection method for human activity recognition using smartphone sensors", MDPI, 2021
More
Mohamed El Sayed Ahmed Muhamed, "Efficient schemes for playout latency reduction in P2P-VOD systems", Springer, 2018
More
Mohamed El Sayed Ahmed Muhamed, "a novel algorithm for source localization based on nonnegative matrix factroization using \alpha 'beta divergence in chochleagram", WSEAS, 2013
More
Mohamed El Sayed Ahmed Muhamed, "Open cluster membership probability based on K-means clustering algorithm", Springer, 2016
More
Department Related Publications
Amr Mohamed Samy Mohammed Mahdi , "Numerical Study for the Fractional Differential Equations Generated by Optimization Problem Using Chebyshev Collocation Method and FDM", Natural Sciences Publishing, USA LLC (NSP), 2013
More
Rodyna Ahmed Mahmoud, "Types of Generalized Open Sets with Ideal", FCS® (Foundation of Computer Science, 2013
More
Rodyna Ahmed Mahmoud, "Some types of compactness via ideal", Research Publication IJSER, 2013
More
Nagla Ameen Mohamed Hssan, "Analysis of multi-level queueing systems with servers breakdown by using recursive solution technique", Published by Elsevier Inc, 2012
More
Usama Abdelhamid Ibrahim, "Convergence of Intuionistic Fuzzy Filters in Syntopogenous Intuionisticfuzzy Strctures", Marsland press, 2013
More
جامعة المنصورة
جامعة الاسكندرية
جامعة القاهرة
جامعة سوهاج
جامعة الفيوم
جامعة بنها
جامعة دمياط
جامعة بورسعيد
جامعة حلوان
جامعة السويس
شراقوة
جامعة المنيا
جامعة دمنهور
جامعة المنوفية
جامعة أسوان
جامعة جنوب الوادى
جامعة قناة السويس
جامعة عين شمس
جامعة أسيوط
جامعة كفر الشيخ
جامعة السادات
جامعة طنطا
جامعة بنى سويف