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Please use this identifier to cite or link to this item:
http://hdl.handle.net/123456789/13368
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| 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) |
| 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: | Institut Matematik Kejuruteraan (Articles)
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