Abstract
We propose a new approach for semantics-based image retrieval. We use color-texture classification to generate the codebook which is used to segment images into regions. The content of a region is characterized by its self-saliency and the lower-level features of the region, including color and texture. The context of regions in an image describes their relationships, which are related to their relative-saliencies. High-level (semantics-based) querying and query-by-example are supported on the basis of the content and context of image regions. The experimental results demonstrate the effectiveness of our approach.
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© 2002 Springer-Verlag Berlin Heidelberg
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Wang, W., Song, Y., Zhang, A. (2002). Semantics-Based Image Retrieval by Region Saliency. In: Lew, M.S., Sebe, N., Eakins, J.P. (eds) Image and Video Retrieval. CIVR 2002. Lecture Notes in Computer Science, vol 2383. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45479-9_4
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DOI: https://doi.org/10.1007/3-540-45479-9_4
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Online ISBN: 978-3-540-45479-3
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