Please use this identifier to cite or link to this item:
http://dspace.unimap.edu.my:80/xmlui/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) |
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://dspace.unimap.edu.my/123456789/13368 |
ISSN: | 0127-8274 |
Appears in Collections: | Institute of Engineering Mathematics (Articles) |
Files in This Item:
File | Description | Size | Format | |
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complete visual based.pdf | 343.75 kB | Adobe PDF | View/Open |
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