A NEW METHOD FOR 3D SHAPE INDEXING AND RETRIEVAL IN LARGE DATABASE BY USING THE LEVEL CUT

In this study, we propose a new method for indexing and retrieval of 3D models in large databases based on binary images extracted from the 3D object called "level cut" LC. These cuts are obtained by the intersection of the set of the plans with the 3D object. A set of equidistant parallel plans generates by the intersection with the 3D object a set of cuts that used to indexing the 3D model. We are based on these cuts to describe the 3D object by using the vectors descriptors based on these cuts. To validate our descriptor we extract a test database from the NTU base. The robustness of our descriptor is well demonstrated by the comparison with the two will known descriptors, the 3D Zernike descriptor and the 3D invariant moment’s descriptor. The topological problem of the external surfaces that representing the 3D object has been confronted, that shows the superiority of the cut method, because it is keeping the external surfaces details of the 3D object during the cutting step.