Abstract
This paper presents a fast exhaustive multi-resolution search algorithm in a clustered image database. Prior to search process, the whole image data set is partitioned into a pre-defined number of clusters having similar feature contents. For a given query, the proposed algorithm first checks the lower bound of distances in each cluster, eliminating disqualified clusters. Next, it only examines the candidates in the surviving clusters through feature matching. Simulation results show that the proposed algorithm guarantees very rapid exhaustive search ...
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© 2004 Springer-Verlag Berlin Heidelberg
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Song, B.C., Chun, K.W. (2004). Clustering-Based Image Retrieval Using Fast Exhaustive Multi-resolution Search Algorithm. In: Aizawa, K., Nakamura, Y., Satoh, S. (eds) Advances in Multimedia Information Processing - PCM 2004. PCM 2004. Lecture Notes in Computer Science, vol 3333. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30543-9_47
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DOI: https://doi.org/10.1007/978-3-540-30543-9_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23985-7
Online ISBN: 978-3-540-30543-9
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