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Cited by 762

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Image classification for content-based indexing

Vailaya, A., Figueiredo, M.A.T., Jain, A.K., Hong-Jiang Zhang·2001·IEEE Transactions on Image Processing
DOI 10.1109/83.892448
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Abstract

Grouping images into (semantically) meaningful categories using low-level visual features is a challenging and important problem in content-based image retrieval. Using binary Bayesian classifiers, we attempt to capture high-level concepts from low-level image features under the constraint that the test image does belong to one of the classes. Specifically, we consider the hierarchical classification of vacation images; at the highest level, images are classified as indoor or outdoor; outdoor images are further classified as city or landscape; finally, a subset of landscape images is classified into sunset, forest, and mountain classes. We demonstrate that a small vector quantizer (whose optimal size is selected using a modified MDL criterion) can be used to model the class-conditional densities of the features, required by the Bayesian methodology. The classifiers have been designed and evaluated on a database of 6931 vacation photographs. Our system achieved a classification accuracy of 90.5% for indoor/outdoor, 95.3% for city/landscape, 96.6% for sunset/forest and mountain, and 96% for forest/mountain classification problems. We further develop a learning method to incrementally train the classifiers as additional data become available. We also show preliminary results for feature reduction using clustering techniques. Our goal is to combine multiple two-class classifiers into a single hierarchical classifier.

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Cited by

Metadata

Authors
Vailaya, A., Figueiredo, M. A. T., Jain, A. K., & Zhang, H.-J.
Venue
IEEE Transactions on Image Processing
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2001
Volume
10
Issue
1
Pages
117-130
ISSN
1057-7149 (ISSN-L)
DOI
10.1109/83.892448
OpenAlex
W2138826255
Cited by
762
References
2
FWCI
31.77
Type
journal article
Language
en
Open access
closed
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)

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