Efficient Region-Based Image Retrieval

Title Efficient Region-Based Image Retrieval
Author(s) R. Weber, M.Mlivoncic
Type Inproceedings
Booktitle 12th International Conference on Information and Knowledge Management (CIKM'03)
New Orleans, LA, USA
Organization Institute of Information Systems, ETH Zurich
Month November
Year 2003


Region-based image retrieval (RBIR) was recently proposed as an extension of content-based image retrieval (CBIR). An RBIR system automatically segments images into a variable number of regions, and extracts for each region a set of features. Then, a dissimilarity function determines the distance between a database image and a set of reference regions. Unfortunately, the large evaluation costs of the dissimilarity function are restricting RBIR to relatively small databases. In this paper, we apply a multi-step approach to enable region-based techniques for large image collections. We provide cheap lower and upper bounding distance functions for a recently proposed dissimilarity measure. As our experiments show, these bounding functions are so tight, that we have to evaluate the expensive distance function for less than 0.5% of the images. For a typical image database with more than 370,000 images, our multi-step approach improved retrieval performance by a factor of more than 5 compared to the currently fastest methods.

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