Generally

normal based shape histogram feature，such as Complex Extend Gaussian Image

is rotation variant for 3D shape. This paper proposed a new kind of normal based shape signature

namely Radius Angle

which can remain invariant under rotation. Then

the Radius Angle Histogram(RAH) is constructed to describe shape contents and used for 3D shape retrievals. The RAH shape descriptor first uses a series of concentric spheres to capture the point distribution information of the given model. Then for points in each concentric sphere

the Radian Normal Angle is computed to extract the local geometry features. Finally

the Radius Normal Histogram is constructed by using the extracted shape signatures. The proposed shape representation remains invariant under rotations. It can be generated from the given 3D model efficiently and easily as well. In addition

this paper discusses the point sampling result’s affect on the final retrieving precision. The voxelization is used to make the sampled point more even over the surface

and better retrieving precision can be achieved by this process. the performance comparisons for the shape benchmark database have proven that the proposed algorithm can achieve better retrieving performance than other similar histogram based shape representations.