Document Type
Conference Proceeding
Publication Date
2-1998
Abstract
The ZEBRA system, which is part of the VisualHarness platform for managing heterogeneous data, supports three types of access to distributed image repositories: keyword based, attribute based, and image content based. A user can assign different weights (relative importance) to each of the three types, and within the last type of access, to each of the image properties. The image based access component (IBAC) supports access based on computable image properties such as those based on spatial domain, frequency domain or statistical and structural analysis. However, it uses a novel black box approach of utilizing a Visual Information Retrieval (VIR) engine to compute corresponding metadata that is then independently managed in a relational database to provide query processing involving image features and information correlation. That is, one overcomes the difficulties in using the feature vectors that are proprietary to a VTR engine, as one does not require any knowledge of the internal representation or format of the image feature used by a VIR engine.
Repository Citation
Mudumbai, S.,
Shah, K.,
Sheth, A. P.,
Parasuraman, K.,
& Bertram, C.
(1998). ZEBRA Image Access System. Proceedings of the 14th International Conference on Data Engineering, 602.
https://corescholar.libraries.wright.edu/knoesis/807
DOI
10.1109/ICDE.1998.655826
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
Presented at the 14th International Conference on Data Engineering, Orlando, FL, February 23-27, 1998.
Posted with permission from IEEE.