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Proceedings Paper

Content-based image retrieval using wavelet-based salient points
Author(s): Qi Tian; Nicu Sebe; Michael S. Lew; E. Loupias; Thomas S. Huang
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Paper Abstract

Content-based image retrieval has become one of the most active research areas in the past few years. Most of the attention from the research has been focused on indexing techniques based on global feature distributions. However, these global distributions have limited discriminating power because they are unable to capture local image information. Applying global Gabor texture features greatly improves the retrieval accuracy. But they are computationally complex. In this paper, we present a wavelet-based salient point extraction algorithm. We show that extracting the color and texture information in the locations given by these points provides significantly improved results in terms of retrieval accuracy, computational complexity and storage space of feature vectors as compared to the global feature approaches.

Paper Details

Date Published: 1 January 2001
PDF: 12 pages
Proc. SPIE 4315, Storage and Retrieval for Media Databases 2001, (1 January 2001); doi: 10.1117/12.410953
Show Author Affiliations
Qi Tian, Univ. of Illinois/Urbana-Champaign (United States)
Nicu Sebe, Leiden Institute of Advanced Computer Science (Netherlands)
Michael S. Lew, Leiden Institute of Advanced Computer Science (Netherlands)
E. Loupias, INSA-Lyon (France)
Thomas S. Huang, Univ. of Illinois/Urbana-Champaign (United States)


Published in SPIE Proceedings Vol. 4315:
Storage and Retrieval for Media Databases 2001
Minerva M. Yeung; Chung-Sheng Li; Rainer W. Lienhart, Editor(s)

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