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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. In: International Conference on Electrical and Electronic Engineering 2015 (IC3E 2015), 10-11 August 2015 , Melaka, Malaysia.


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Implementation of neural network for acoustic computation is not new. 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 classified 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 higher accuracy compared to the BP algorithm, managed to record highest accuracy of 88% as opposed to 81.3% for the latter.

Item Type: Conference or Workshop Item (Paper)
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: Normajihan Abd. Rahman
Date Deposited: 26 Oct 2015 07:23
Last Modified: 26 Oct 2015 07:23
URI: http://eprints.uthm.edu.my/id/eprint/7190
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