Abstract
Object recognition and categorization are two important key features of computer vision. Accuracy aspects represent research challenge for both object recognition and categorization techniques. High performance computing (HPC) technologies usually manage the increasing time and complexity of computations. In this paper, a new approach that use 3D spin-images for 3D object categorization is introduced. The main contribution of our approach is that it employs the MPI techniques in a unique way to extract spin-images. The technique proposed utilizes the independence between spin-images generated at each point. Time estimation of our technique have shown dramatic decrease of the categorization time proportional to number of workers used.