A LEARNING APPROACH TO CONTENT-BASED IMAGE CATEGORIZATION AND RETRIEVAL

Washington Mio, Yuhua Zhu, Xiuwen Liu

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.

Download


Paper Citation


in Harvard Style

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 - Volume 2: VISAPP, ISBN 978-972-8865-74-0, pages 36-43. DOI: 10.5220/0002046700360043


in Bibtex Style

@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 - Volume 2: VISAPP,},
year={2007},
pages={36-43},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002046700360043},
isbn={978-972-8865-74-0},
}


in EndNote Style

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