针对3维模型检索算法性能较低的问题，提出了一种基于整数中轴骨架的3维模型检索算法。在对3维模型进行姿态调整和各向同向性预处理后，提取模型的整数中轴骨架，并记录每个骨架点相应的几何信息，对提取的骨架按不同的空间区域划分，形成模型骨架二叉树。为了能够描述骨架二叉树的不同节点对模型整体相似性匹配的影响程度，为每个节点定义一个特征权值，其大小由该节点对应的骨架区域大小所决定。最后，采用由粗到细逐步淘汰的策略计算不同模型的相似度。对一个标准3维模型测试数据库的检索实验结果表明，由于将模型的拓扑结构和统计特征相结合，该算法可以得到较好的检索性能。

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.