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dc.contributor.authorMuhammad Khusairi, Osman
dc.contributor.authorMohd Yusoff, Mashor, Prof. Dr.
dc.contributor.authorMohd Rizal, Arshad
dc.date.accessioned2014-06-04T04:21:32Z
dc.date.available2014-06-04T04:21:32Z
dc.date.issued2004-12
dc.identifier.citationp. 1011-1015en_US
dc.identifier.isbn0-7803-8643-4
dc.identifier.urihttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1460727&tag=1
dc.identifier.urihttp://dspace.unimap.edu.my:80/dspace/handle/123456789/35051
dc.descriptionProceeding of The International Conference on Computer Graphics, Imaging and Visualization 2004 at Singapore on 1 December 2004 through 3 December 2004. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp?tag=1en_US
dc.description.abstractThis paper proposes an effective method for recognition and classification of 3D objects using multiple views technique and neural networks system. In the processing stage, we propose to use 2D moment invariants as the features for modeling 3D objects. 2D moments have been commonly used for 2D object recognition. However, we have proved that with some adaptation to multiple views technique, 2D moments are sufficient to model 3D objects. In addition, the simplicity of 2D moments calculation reduces the processing time for feature extraction, hence increases the system efficiency. In the recognition stage, we propose a cascaded multilayered perceptron (c-MLP) network for matching and classification. The c-MLP contains two MLP networks which are arranged in a serial combination. This proposed method has been tested using two groups of object, polyhedral and free-form objects. We also compare our method with standard MLP network. Our results show that the proposed method can successfully be applied to 3D object recognition. In addition, the proposed network also achieved better performance and faster convergence rate compared to the than standard MLP.en_US
dc.language.isoenen_US
dc.publisherIEEE Conference Publicationsen_US
dc.relation.ispartofseriesProceeding of The IEEE Conference on Cybernetics and Intelligent Systems 2004;
dc.subjectObject recognitionen_US
dc.subjectCascade Multilayered Perceptron (c-MLP)en_US
dc.subjectThree dimensional (3d) object recognition systemsen_US
dc.subjectVision systemsen_US
dc.title3D object recognition system using multiple views and cascaded multilayered perceptron networken_US
dc.typeWorking Paperen_US
dc.identifier.urlhttp://dx.doi.org/10.1109/ICCIS.2004.1460727
dc.contributor.urlkhusairi@eng.usm.myen_US
dc.contributor.urlyusoff@unimap.edu.myen_US
dc.contributor.urlrizal@eng.usm.myen_US
Appears in Collections:Mohd Yusoff Mashor, Prof. Dr.



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