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Automated classification of galaxies using invariant moments
conference contribution
posted on 2023-05-23, 07:39 authored by Elfattah, MA, Abu Elsoud, MA, Hassanien, AE, Kim, THClassification and identification of galaxy shape is an important issue for astronauts since it provides valuable information about the origin and the evolution of the universe. Statistical invariant features that are functions of moments have been used as global features of galaxy images in their pattern recognition. In this paper, an automated training based recognition system that can compute the statistical invariant features for different galaxy shapes is investigated. The proposed algorithm is robust, regardless of orientation, size and position of the galaxy inside the image. Feature vectors are computed via nonlinear moment invariant functions for each galaxy shape. After feature extraction, the recognition performance of classifier in conjunction with these moment–based features is introduced. Computer simulations show that Galaxy images are classified with an accuracy of about 90% compared to the human visual classification system.
History
Publication title
Proceedings of the 4th International Conference on Future Generation Information TechnologyEditors
T-H Kim, Y-H Lee and W-C FangPagination
103-111ISBN
978-3-642-35584-4Department/School
School of Information and Communication TechnologyPublisher
SpringerPlace of publication
New York, United StatesEvent title
4th International Conference on Future Generation Information TechnologyEvent Venue
Gangneung, Kangwondo, KoreaDate of Event (Start Date)
2012-12-16Date of Event (End Date)
2012-12-19Rights statement
Copyright 2012 Springer-Verlag Berlin HeidelbergRepository Status
- Restricted