  The recent technological progress in acquisition, modeling and processing of
3D data leads to the proliferation of a large number of 3D objects databases.
Consequently, the techniques used for content based 3D retrieval has become
necessary. In this paper, we introduce a new method for 3D objects recognition
and retrieval by using a set of binary images CLI (Characteristic level
images). We propose a 3D indexing and search approach based on the similarity
between characteristic level images using Hu moments for it indexing. To
measure the similarity between 3D objects we compute the Hausdorff distance
between a vectors descriptor. The performance of this new approach is evaluated
at set of 3D object of well known database, is NTU (National Taiwan University)
database.
