3D image retrieval based on differential geometry and co-occurrence matrix |
| |
Authors: | Kehua Guo Guihua Duan |
| |
Affiliation: | 1. School of Information Science and Engineering, Central South University, Changsha, China
|
| |
Abstract: | 3D image retrieval approach is a challenging problem in the research of content-based image retrieval. In this paper, a novel retrieval approach combined differential geometry and co-occurrence matrix is presented. Firstly, Gaussian curvature and mean curvature are utilized to represent the inherent characteristic of spatial surface, and then we use co-occurrence matrix to store the shape information of 3D images. Secondly, normalization process is applied to the co-occurrence matrix and the invariants independence of the translation, scaling, and rotation transforms are proved. In comparison with the recent methods, experiments indicate a lower computation complexity and a better retrieval rate to 3D images with slight different shape characteristic. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|