An information-driven framework for image mining
Paper
Paper/Presentation Title | An information-driven framework for image mining |
---|---|
Presentation Type | Paper |
Authors | Zhang, Ji (Author), Hsu, Wynne (Author) and Lee, Mong Li (Author) |
Editors | Mayr, Heinrich C., Lazansky, Jiri, Quirchmayr, Gerald and Vogel, Pavel |
Journal or Proceedings Title | Lecture Notes in Computer Science (Book series) |
Journal Citation | 2113, pp. 232-242 |
Number of Pages | 7 |
Year | 2001 |
Publisher | Springer |
Place of Publication | Germany |
ISSN | 1611-3349 |
0302-9743 | |
ISBN | 9783540425274 |
Digital Object Identifier (DOI) | https://doi.org/10.1007/3-540-44759-8_24 |
Web Address (URL) of Paper | https://link.springer.com/chapter/10.1007/3-540-44759-8_24 |
Conference/Event | 12th International Conference on Database and Expert Systems Applications (DEXA'01) |
Event Details | 12th International Conference on Database and Expert Systems Applications (DEXA'01) Event Date 03 to end of 05 Sep 2001 Event Location Munich, Germany |
Abstract | Image mining systems that can automatically extract semantically meaningful information (knowledge) from image data are increasingly in demand. The fundamental challenge in image mining is to determine how low-level, pixel representation contained in a raw image or image sequence can be processed to identify high-level spatial objects and relationships. To meet this challenge, we propose an efficient information-driven framework for image mining. We distinguish four levels of information: the Pixel Level, the Object Level, the Semantic Concept Level, and the Pattern and Knowledge Level. High-dimensional indexing schemes and retrieval techniques are also included in the framework to support the flow of information among the levels. We believe this framework represents the first step towards capturing the different levels of information present in image data and addressing the issues and challenges of discovering useful |
Keywords | image mining systems |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
Public Notes | File reproduced in accordance with the copyright policy of the publisher/author. |
Byline Affiliations | National University of Singapore |
https://research.usq.edu.au/item/9z2v1/an-information-driven-framework-for-image-mining
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