A LEARNING APPROACH TO CONTENT-BASED IMAGE CATEGORIZATION AND RETRIEVAL

Washington Mio; Yuhua Zhu; Xiuwen Liu

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Paper

A LEARNING APPROACH TO CONTENT-BASED IMAGE CATEGORIZATION AND RETRIEVAL

Topics: Object, Event and Scene Recognition, Retrieval and Indexing; Recognition and Indexing

In Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, 36-43, 2007 , Barcelona, Spain

Authors: Washington Mio ; Yuhua Zhu and Xiuwen Liu

Affiliation: Florida State University, United States

Keyword(s): Content-based image retrieval, image categorization, image indexing, machine learning, spectral components, dimension reduction, discriminant analysis.

Abstract: We develop a machine learning approach to content-based image categorization and retrieval. We represent images by histograms of their spectral components associated with a bank of filters and assume that a training database of labeled images – that contains representative samples from each class – is available. We employ a linear dimension reduction technique, referred to as Optimal Factor Analysis, to identify and split off “optimal” low-dimensional factors of the features to solve a given semantic classification or indexing problem. This content-based categorization technique is used to structure databases of images for retrieval according to the likelihood of each class given a query image.

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Paper citation in several formats:

Mio, W.; Zhu, Y. and Liu, X. (2007). A LEARNING APPROACH TO CONTENT-BASED IMAGE CATEGORIZATION AND RETRIEVAL. In Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISIGRAPP 2007) - Volume 2: VISAPP; ISBN 978-972-8865-74-0; ISSN 2184-4321, SciTePress, pages 36-43. DOI: 10.5220/0002046700360043

@conference{visapp07,
author={Washington Mio. and Yuhua Zhu. and Xiuwen Liu.},
title={A LEARNING APPROACH TO CONTENT-BASED IMAGE CATEGORIZATION AND RETRIEVAL},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISIGRAPP 2007) - Volume 2: VISAPP},
year={2007},
pages={36-43},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002046700360043},
isbn={978-972-8865-74-0},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISIGRAPP 2007) - Volume 2: VISAPP
TI - A LEARNING APPROACH TO CONTENT-BASED IMAGE CATEGORIZATION AND RETRIEVAL
SN - 978-972-8865-74-0
IS - 2184-4321
AU - Mio, W.
AU - Zhu, Y.
AU - Liu, X.
PY - 2007
SP - 36
EP - 43
DO - 10.5220/0002046700360043
PB - SciTePress