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Proceedings Paper

Discovering spatial associations in images
Author(s): Osmar R. Zaiane; Jiawei Han
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Paper Abstract

In this paper, our focus in data mining is concerned with the discovery of spatial associations within images. Our work concentrates on the problem of finding associations between visual content in large image databases. Discovering association rules has been the focus of many studies in the last few years. However, for multimedia data such as images or video frames, the algorithms proposed in the literature are not sufficient since they miss relevant frequent item-sets due to the peculiarity of visual data, like repetition of features, resolution levels, etc. We present in this paper an approach for mining spatial relationships from large visual data repositories. The approach proceeds in three steps: feature localization, spatial relationship abstraction, and spatial association discovery. The mining process considers the issue of scalability and contemplates various feature localization abstractions at different resolution levels.

Paper Details

Date Published: 6 April 2000
PDF: 10 pages
Proc. SPIE 4057, Data Mining and Knowledge Discovery: Theory, Tools, and Technology II, (6 April 2000); doi: 10.1117/12.381726
Show Author Affiliations
Osmar R. Zaiane, Univ. of Alberta (Canada)
Jiawei Han, Simon Fraser Univ. (Canada)


Published in SPIE Proceedings Vol. 4057:
Data Mining and Knowledge Discovery: Theory, Tools, and Technology II
Belur V. Dasarathy, Editor(s)

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