Recognition of 3D Objects from 2D Views Features

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.