Discovering spatial associations in images

Osmar R. Zaiane; Jiawei Han

doi:10.1117/12.381726

6 April 2000 Discovering spatial associations in images

Osmar R. Zaiane, Jiawei Han

Proceedings Volume 4057, Data Mining and Knowledge Discovery: Theory, Tools, and Technology II; (2000) https://doi.org/10.1117/12.381726
Event: AeroSense 2000, 2000, Orlando, FL, United States

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.

Citation Download Citation

Osmar R. Zaiane and Jiawei Han "Discovering spatial associations in images", Proc. SPIE 4057, Data Mining and Knowledge Discovery: Theory, Tools, and Technology II, (6 April 2000); https://doi.org/10.1117/12.381726

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