Theory of keyblock-based image retrieval
ACM Transactions on Information Systems (TOIS)
SemQuery: Semantic Clustering and Querying on Heterogeneous Features for Visual Data
IEEE Transactions on Knowledge and Data Engineering
Advanced feature extraction for keyblock-based image retrieval
Information Systems
| Hi-index | 0.00 |
Besides traditional applications (e.g., CAD/CAM and Trademark registry), new multimedia applications such as structured video, animation, and MPEG-4 standard require the storage and management of well-defined objects. For efficient retrieval of 2D objects by shape, we propose three index structures on features that are extracted from the objects' minimum bounding circles (MBC). A major observation is that those features are unique per object and can be utilized to filter out non-similar candidates. To evaluate our techniques, we conducted a simulation study on a database of 2D objects. The results show the superiority of our techniques as compared to a naive indexing (at least 40% improvement in I/O cost). We also identify one of the indexing structures as the superior one, independent of the size of the database and the number of vertices of the objects.