dc.contributor.author | Mohd Syafarudy, Abu | |
dc.contributor.author | Lim, Eng Aik | |
dc.date.accessioned | 2011-08-02T03:46:24Z | |
dc.date.available | 2011-08-02T03:46:24Z | |
dc.date.issued | 2009 | |
dc.identifier.citation | MATEMATIKA, vol. 25(2), 2009, pages 147–156 | en_US |
dc.identifier.issn | 0127-8274 | |
dc.identifier.uri | http://www.fs.utm.my/matematika/images/stories/matematika/20092526.pdf | |
dc.identifier.uri | http://dspace.unimap.edu.my/123456789/13368 | |
dc.description | Link to publisher's homepage at http://www.utm.my/ | en_US |
dc.description.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. | en_US |
dc.language.iso | en | en_US |
dc.publisher | University Teknologi Malaysia (UTM) | en_US |
dc.subject | Coin-Counting | en_US |
dc.subject | Feature extraction | en_US |
dc.subject | Median filter | en_US |
dc.subject | Edge detection | en_US |
dc.subject | Image segmentation | en_US |
dc.title | Visual based automatic coin counting system using neural network | en_US |
dc.type | Article | en_US |
dc.publisher.department | Department of Mathematics | en_US |