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Machine Learning Methods in Automatic Image Annotation

  • Chapter
Advances in Machine Learning II

Part of the book series: Studies in Computational Intelligence ((SCI,volume 263))

Abstract

Machine learning methods are successfully applied in many branches of Computer Science. One of these branches is image analysis, and being more specific – Automatic Image Annotation. Automatic Image Annotation was found an important research domain several years ago. It grew from such research domains as image recognition and cross-lingual machine translation. Increase of computational, data storage and data transfer abilities of todays’ computers has been one of key factors, making Automatic Image Annotation possible. Automatic Image Annotation methods, which have appeared during last several years, make a large use of many machine learning approaches. Clustering and classification methods are most frequently applied to annotate images. The chapter consists of three main parts. In the first, some general information concerning annotation methods is presented. In the second part, two original annotation methods are described. The last part presents experimental studies of the proposed methods.

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Author information

Authors and Affiliations

  1. Wroclaw University of Technology, Wroclaw, Poland

    Halina Kwaśnicka & Mariusz Paradowski

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  1. Halina Kwaśnicka
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  2. Mariusz Paradowski
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Editors and Affiliations

  1. Institute of Computer Science, Polish Academy of Sciences, ul. Ordona 21, 01-237, Warsaw, Poland

    Jacek Koronacki  & Sławomir T. Wierzchoń  & 

  2. Woodward Hall 430C, University of North Carolina, 9201 University City Blvd., N.C. 28223, Charlotte, USA

    Zbigniew W. Raś

  3. Systems Research Institute, Polish Academy of Sciences, ul.Newelska 6, 01-447, Warsaw, Poland

    Janusz Kacprzyk

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Kwaśnicka, H., Paradowski, M. (2010). Machine Learning Methods in Automatic Image Annotation. In: Koronacki, J., Raś, Z.W., Wierzchoń, S.T., Kacprzyk, J. (eds) Advances in Machine Learning II. Studies in Computational Intelligence, vol 263. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05179-1_18

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  • DOI: https://doi.org/10.1007/978-3-642-05179-1_18

  • Publisher Name: Springer, Berlin, Heidelberg

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  • Online ISBN: 978-3-642-05179-1

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