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Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/10134
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dc.contributor.authorMohd Yusof, Mashor, Prof. Dr.-
dc.contributor.authorM. K., Osman-
dc.contributor.authorR., Arshad-
dc.date.accessioned2010-11-01T01:43:09Z-
dc.date.available2010-11-01T01:43:09Z-
dc.date.issued2007-08-
dc.identifier.citationp.8-9en_US
dc.identifier.issn1823-9633-
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/10134-
dc.description.abstractComputer vision recognition typically involves sensors, a model database containing information about the object representations and decision making or categorization. Sensors gather images that are processed to represent it as the database models and a recognition algorithm is applied to find the model to which the object best matches, known as model-based object recognition system.en_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Perlis (UniMAP)en_US
dc.relation.ispartofseriesExploreen_US
dc.relation.ispartofseriesAugust 2007en_US
dc.subjectExplore -- Penerbitan universitien_US
dc.subjectUniMAP -- Publicationsen_US
dc.subjectUniMAP -- Research and developmenten_US
dc.subject3D objectsen_US
dc.subjectRecognition systemen_US
dc.title3D object recognition: Views, moment invariants & perceptron networksen_US
dc.typeArticleen_US
dc.publisher.departmentPejabat Timbalan Naib Canselor (Penyelidikan dan Inovasi)en_US
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Mohd Yusoff Mashor, Prof. Dr.

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