Using a Partial Geometric Feature for Similarity Search of 3D Objects

Searching a database of 3D objects for objects that are similar to a given 3D search object is an important task that arises in a number of database applications for example, in Medicine and CAD fields. Most of the existing similarity models are based on global features of 3D objects. Developing a feature set or a feature vector of 3D object using their partial features is challenging. In the present paper, we introduce a novel segment weight vector to matching 3D objects rapidly. We also describe a partial and geometrical similarity based solution to the problem of searching for similar 3D objects. As the first step, we split a 3D object into parts according to its topology. Next, we introduce a new method to extract the thickness feature of each part and generate the feature as a feature vector of the 3D object. We also propose a novel searching algorithm using the newly introduced feature vector. Furthermore, we present a new solution for improving the accuracy of the similarity queries. Finally, we present a performance evaluation of our stratagem. The result indicates that the proposed approach offers a significant performance improvement over the existing approach. Since the proposed method is based on partial features, it is particularly suited to searching objects having distinct part structures and is invariant to part architecture.