Intelligent system for bar detection based on Non-negative Matrix Factorization Algorithms | ||||
| International Journal of Advanced Engineering and Business Sciences | ||||
| Volume 3, Issue 3, October 2022, Page 35-51 PDF (677.26 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/ijaebs.2022.160768.1034 | ||||
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| Authors | ||||
Ibrahim Selim1; shimaa nawar elbably  2; walid dabour2
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| 1Dept. of CS Faculty of Computer and Artificial Intelligence, University of Sadat City | ||||
| 2Math and Computer Science Dept., Faculty of Science, Menoufia University, Egypt | ||||
| Abstract | ||||
| In this paper , a new automated machine supervised learning method for bar detection scheme in spiral galaxies based on the Non-negative Matrix Factorization algorithm have been presented and tested. Non-negative matrix factorization has been introduced in this paper to detection bar in spiral galaxies, which is very easy to use , and gives us a good accuracy in a little time. Detection bar in spiral galaxies is the main objective of this research. WE describe an entirely automated method that extract feature from spiral galaxies and then automatically bar detection . The algorithm is trained using manually bared and non-bared images of spiral galaxies. The algorithm show that the bar in spiral images from the EFIGI catalog can be detected automatically with an accuracy of 97.3% with an average processing time of 0.37 s per galaxy compared to bar detection carried out by other authors and manually detection . | ||||
| Keywords | ||||
| Spiral Galaxies; barred spiral classification; Nonnegative matrix factorization (NMF); image processing; Machine learning | ||||
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