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Recognition of 3D Objects from 2D Views Features

Author

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  • R. Khadim

    (Faculty of Science and Technology, Université Sultan Moulay Slimane, Beni Mellal, Morocco)

  • R. El Ayachi

    (Faculty of Science and Technology, Université Sultan Moulay Slimane, Beni Mellal, Morocco)

  • Mohamed Fakir

    (Faculty of Science and Technology, Université Sultan Moulay Slimane, Beni Mellal, Morocco)

Abstract

This paper focuses on the recognition of 3D objects using 2D attributes. In order to increase the recognition rate, the present an hybridization of three approaches to calculate the attributes of color image, this hybridization based on the combination of Zernike moments, Gist descriptors and color descriptor (statistical moments). In the classification phase, three methods are adopted: Neural Network (NN), Support Vector Machine (SVM), and k-nearest neighbor (KNN). The database COIL-100 is used in the experimental results.

Suggested Citation

  • R. Khadim & R. El Ayachi & Mohamed Fakir, 2015. "Recognition of 3D Objects from 2D Views Features," Journal of Electronic Commerce in Organizations (JECO), IGI Global, vol. 13(2), pages 50-58, April.
    • Handle: RePEc:igg:jeco00:v:13:y:2015:i:2:p:50-58
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