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Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/dspace/handle/123456789/13368

Title: Visual based automatic coin counting system using neural network
Authors: Mohd Syafarudy, Abu
Lim, Eng Aik
Keywords: Coin-Counting;Feature extraction;Median filter;Edge detection;Image segmentation
Issue Date: 2009
Publisher: University Teknologi Malaysia (UTM)
???metadata.dc.publisher.department???: Department of Mathematics
Citation: MATEMATIKA, vol. 25(2), 2009, pages 147–156
Abstract: A new intelligent coin-counting system is described in this paper. The proposed system is effective and flexible for the purpose of performing coin-counting using image captured from webcam. Image processing techniques are employed to prepare data for image understanding, and a Radial Basis Function (RBF) network is employed for performing the classification task. Extensive and promising results were obtained and the analysis suggests the proposed Radial Basis Function type classifier provides good results for high accuracy in coin-counting.
Description: Link to publisher's homepage at http://www.utm.my/
URI: http://www.fs.utm.my/matematika/images/stories/matematika/20092526.pdf
http://hdl.handle.net/123456789/13368
ISSN: 0127-8274
Appears in Collections:Institute of Engineering Mathematics (Articles)

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