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PSO-BP algorithm implementation for material surface image identification

Zainudin, Fathin Liyana and Mahamad, Abd Kadir and Saon, Sharifah and Yahya, Musli Nizam (2015) PSO-BP algorithm implementation for material surface image identification. ARPN Journal of Engineering and Applied Sciences, 10 (19). pp. 8853-8857. ISSN 18196608


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Implementation of neural network for acoustic computation is not ne w. In this paper, a new improved method in predicting material surface from photographic image was implemented using a hybrid of particle swarm optimization and back-propagation neural network (PSO-BP) algorithm. Before the system clas sified the data using PSO-BP algorithm, the photographic images of room surfaces need to be extracted using Gray Level Co-occurrence Matrix (GLCM) and Modified Zernike Moments. The result indicated that the PSO-BP algorithm have a hig her accuracy compared to the BP algorithm, managed to record highest accuracy of 88% as opposed to 81.3% for the latter.

Item Type: Article
Uncontrolled Keywords: Particle swarm optimization; back-propagation; image processing
Subjects: Q Science > QC Physics
Divisions: Faculty of Electrical and Electronic Engineering > Department of Computer Engineering
Depositing User: Mr. Mohammad Shaifulrip Ithnin
Date Deposited: 13 Aug 2018 03:37
Last Modified: 13 Aug 2018 03:37
URI: http://eprints.uthm.edu.my/id/eprint/9393
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