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An Empirical Study on Large-Scale Content-Based Image Retrieval

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3 Author(s)
Yuk Man Wong ; Department of Computer Science & Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong S.A.R., China, Email: ; Steven C. H. Hoi ; Michael R. Lyu

One key challenge in content-based image retrieval (CBIR) is to develop a fast solution for indexing high-dimensional image contents, which is crucial to building large-scale CBIR systems. In this paper, we propose a scalable content-based image retrieval scheme using locality-sensitive hashing (LSH), and conduct extensive evaluations on a large image testbed of a half million images. To the best of our knowledge, there is less comprehensive study on large-scale CBIR evaluation with a half million images. Our empirical results show that our proposed solution is able to scale for hundreds of thousands of images, which is promising for building Web-scale CBIR systems.

Published in:

2007 IEEE International Conference on Multimedia and Expo

Date of Conference:

2-5 July 2007