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Creating New Medical Ontologies for Image Annotation pp 91–102Cite as

Semantic-Based Image Retrieval

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Part of the book series: SpringerBriefs in Electrical and Computer Engineering ((BRIEFSELECTRIC))

Abstract

An active development of semantic-based visual information retrieval methods was made in an attempt to reduce the semantic gap. The semantic-based image retrieval task aims to discover high-level semantic meaning within an image. The main obstacle in realizing semantic-based image retrieval activities is represented by the fact that it is very difficult to describe the semantic content of an image. In this chapter, we are presenting an overview of existing methods that can be applied for semantic-based image retrieval and also a description of the experimental results we have obtained after using the two models for semantic-based image retrieval provided by cross-media relevance model. Given a query word, the first model is using a language-modeling approach to rank the images from a training set. The second model is using an approach based on query expansion to rank the images being more effective than the previous one.

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Authors and Affiliations

  1. Department of Software Engineering, University of Craiova, Craiova, 200585, Romania

    Liana Stanescu, Dumitru Dan Burdescu, Marius Brezovan & Cristian Gabriel Mihai

Authors
  1. Liana Stanescu
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  2. Dumitru Dan Burdescu
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  3. Marius Brezovan
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  4. Cristian Gabriel Mihai
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Correspondence to Liana Stanescu .

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Stanescu, L., Burdescu, D.D., Brezovan, M., Mihai, C.G. (2012). Semantic-Based Image Retrieval. In: Creating New Medical Ontologies for Image Annotation. SpringerBriefs in Electrical and Computer Engineering(). Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1909-9_6

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  • DOI: https://doi.org/10.1007/978-1-4614-1909-9_6

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-1908-2

  • Online ISBN: 978-1-4614-1909-9

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