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Semantic Image Representation and Indexing

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Encyclopedia of Multimedia

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Definition:Besides low-level visual features, such as color, texture, and shapes, high-level semantic information is useful and effective in image retrieval and indexing.

Low-level visual features such as color, texture, and shapes can be easily extracted from images to represent and index image content [1, 2, 3]. However, they are not completely descriptive for meaningful retrieval. High-level semantic information is useful and effective in retrieval. But it depends heavily on semantic regions, which are difficult to obtain themselves. Between low-level features and high-level semantic information, there is an unsolved “semantic gap” [4].

The semantic gap is due to two inherent problems. One problem is that the extraction of complete semantics from image data is extremely hard as it demands general object recognition and scene understanding. Despite encouraging recent progress in object detection and recognition [5, 6], unconstrained broad image domain still remains a challenge for...

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Authors and Affiliations

  1. Institute for Infocomm Research, Singapore, Singapore

    Joo-Hwee Lim

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  1. Joo-Hwee Lim
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Editors and Affiliations

  1. Florida Atlantic University, Boca Raton, USA

    Borko Furht (Editor-in-Chief) (Editor-in-Chief)

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© 2006 Springer Science+Business Media, Inc.

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Lim, JH. (2006). Semantic Image Representation and Indexing. In: Furht, B. (eds) Encyclopedia of Multimedia. Springer, Boston, MA. https://doi.org/10.1007/0-387-30038-4_217

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