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DEXA
2001
Springer

An Information-Driven Framework for Image Mining

14 years 3 months ago
An Information-Driven Framework for Image Mining
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 patterns/knowledge from each level.
Ji Zhang, Wynne Hsu, Mong-Li Lee
Added 28 Jul 2010
Updated 28 Jul 2010
Type Conference
Year 2001
Where DEXA
Authors Ji Zhang, Wynne Hsu, Mong-Li Lee
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