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.
CITATION STYLE
Wang, W., Song, Y., & Zhang, A. (2002). Semantics-based image retrieval by region saliency. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2383, pp. 29–37). Springer Verlag. https://doi.org/10.1007/3-540-45479-9_4
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