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 base d on binary images extracted from the 3D object called “ level cut” LC. These cuts are obtained by the inter section of the set of the plans with the 3D object. A set of e quidistant parallel plans generates by the intersec tion with the 3D object a set of cuts that used to indexing the 3D m odel. 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 databa se 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 i nvariant moment’s descriptor. The topological problem of the external surfaces that representing the 3D object h as been confronted, that shows the superiority of t he cut method, because it is keeping the external surfaces details of the 3D object during the cutting step.