多特征结合相似度优化的三维工程模型检索算法

3D engineering model retrieval algorithm based on multiple features and similarity calculation optimization

为提高三维模型的检索准确度,针对工程三角网格模型提出了一种基于随机点间距离和法向夹角余弦联合分布及二进制粒子群优化的检索算法。在模型表面构造若干随机点并计算各点之间的距离和法向夹角余弦,然后以距离和余弦为坐标轴建立距离一余弦二维网格,统计各网格中的随机点数量,得到三维模型的距离-余弦联合形状分布矩阵,用分布矩阵之间的L_2距离表示模型之间的相似度。为了体现形状分布矩阵中各元素对模型相似度影响的差异性,采用一种基于二进制粒子群优化的方法对相似度计算过程进行了改进。实验结果表明,本算法可有效提高工程三角网格模型检索的准确性。

This paper proposes a retrieval algorithm based on the binary particle swarm optimization （ PSO） and the joint distribution including the distance between every two random points and the normal included angle cosine in or-der to improve the retrieval accuracy of 3D engineering triangular mesh model. Firstly, numerous sample points on the surface of the model are randomly chosen. Next, the distances and the cosine values of the normal angles among the sample points are calculated. Finally, a two-dimensional grid with the distance and the cosine value as the coordinate axes is established. The joint distance-cosine shape distribution matrix of the 3D model is constructed through the sta-tistic data of sample points acquired in each mesh, using the distance L2 between distribution matrixes to represent similarity between models. In order to demonstrate the different influence of shape distribution elements on the simi-larity in 3D models efficiently, binary PSO is employed to ameliorate the similarity computing process. Experimental results showed that the approach could improve the retrieval accuracy of engineering mesh models effectively.