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dc.contributor.authorMohd Syafarudy, Abu
dc.contributor.authorLim, Eng Aik
dc.date.accessioned2011-08-02T03:46:24Z
dc.date.available2011-08-02T03:46:24Z
dc.date.issued2009
dc.identifier.citationMATEMATIKA, vol. 25(2), 2009, pages 147–156en_US
dc.identifier.issn0127-8274
dc.identifier.urihttp://www.fs.utm.my/matematika/images/stories/matematika/20092526.pdf
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/13368
dc.descriptionLink to publisher's homepage at http://www.utm.my/en_US
dc.description.abstractA 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.isoenen_US
dc.publisherUniversity Teknologi Malaysia (UTM)en_US
dc.subjectCoin-Countingen_US
dc.subjectFeature extractionen_US
dc.subjectMedian filteren_US
dc.subjectEdge detectionen_US
dc.subjectImage segmentationen_US
dc.titleVisual based automatic coin counting system using neural networken_US
dc.typeArticleen_US
dc.publisher.departmentDepartment of Mathematicsen_US


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