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Mining Visual Associations from User Feedback for Weighting Multiple Indexes in Geospatial Image Retrieval

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3 Author(s)
Klaric, M. ; Dept. of Comput. Sci., Univ. of Missouri-Columbia, Columbia, MO ; Scott, G. ; Chi-Ren Shyu

Geospatial content-based image retrieval (CBIR) systems can be used to query for visually similar images by identifying similar patterns between a query image and those in the database. When several different classes of features are used, some queries require that each class should be given a different degree of weight; to this end, CBIR indexes are built for each class of features. This paper proposes an approach for weighting multiple indexes in a geospatial CBIR system by mining information from user feedback. After a small number of iterations of relevance feedback and data mining, index weights can be determined dynamically per query. Using this technique geospatial retrieval system precision of results increased from 70% to 79% after 5 iterations of feedback.

Published in:

Geoscience and Remote Sensing Symposium, 2006. IGARSS 2006. IEEE International Conference on

Date of Conference:

July 31 2006-Aug. 4 2006