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Multi-counterpropagation network model for colour recognition


Citation

Yaakob, Razali and Sulaiman, Md. Nasir and Mahmod, Ramlan and Tengku Muda Mohamed, Mahmud and Ramli, Abd Rahman (1999) Multi-counterpropagation network model for colour recognition. Malaysian Journal of Computer Science, 12 (1). pp. 38-46. ISSN 0127-9084

Abstract / Synopsis

Minolta Chroma Meters was used to convert colours into numbers. It offers five different colour systems for measuring absolute chromaticity, that is, CIE Yxy, L*a*b*, L*C*H°, Hunter Lab and XYZ. In this study, only L*a*b* is used, and combinations of two counterpropagation network (CPN) are required to recognise 808 colours produced by The Royal Horticultural Society, based on RHS Colour Chart [1]. Our proposed neural network model is tested; the result shows that 99% of trained data are recognised, against 98% for untrained data.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Agriculture
Faculty of Computer Science and Information Technology
Faculty of Engineering
Publisher: Faculty of Computer Science and Information Technology, University of Malaya
Keywords: CPN model; Competitive layer; Unsupervised learning; Supervised learning; Minolta Chroma Meters
Depositing User: Nabilah Mustapa
Date Deposited: 30 Dec 2016 10:49
Last Modified: 30 Dec 2016 10:49
URI: http://psasir.upm.edu.my/id/eprint/49453
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