Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/13368
Full metadata record
DC FieldValueLanguage
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
Appears in Collections:Institute of Engineering Mathematics (Articles)

Files in This Item:
File Description SizeFormat 
complete visual based.pdf343.75 kBAdobe PDFView/Open


Items in UniMAP Library Digital Repository are protected by copyright, with all rights reserved, unless otherwise indicated.