To improve the efficiency of 3D model retrieval

an algorithm for 3D model retrieval based on integer medial axis skeleton was proposed in this paper. The integer medial axis skeleton and the geometric information of skeleton point were obtained after the preprocessing of the model. The binary tree of this skeleton was acquired by decomposing the skeleton into a set of blocks by spatial region. To describe the influence of different node of the skeleton binary tree to the similarity matching

the feature weight was defined for each node. Furthermore

the weights were determined by corresponding skeleton region of the 3D model. Finally

a coarse-to-fine strategy was presented to calculate similarity between different 3D models. Differing from other algorithms applied in 3D model retrieval

this algorithm extracts statistical features as well as topological features. The experiments have been carried on a standard testing database of 3D models

and the results show that this algorithm can achieve better retrieving efficiency than other algorithms.