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Proceedings Paper

Approach to clustering large visual databases using wavelet transform
Author(s): Gholamhosein Sheikholeslami; Aidong Zhang
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Paper Abstract

Many applications demand the capability of retrieval based on image content. A classification mechanism is needed to categorize images based on feature similarity. An effective classification of the images can support efficient retrieval of images. In this paper, we investigate a feature-based approach to image clustering and retrieval. Four different texture-based feature sets of images are extracted using Haar and Daubechies wavelet transforms. Using multi- resolution property of wavelets, we extract the features at different levels. The experimental results of our clustering approach on air photo images are reported.

Paper Details

Date Published: 9 April 1997
PDF: 12 pages
Proc. SPIE 3017, Visual Data Exploration and Analysis IV, (9 April 1997); doi: 10.1117/12.270327
Show Author Affiliations
Gholamhosein Sheikholeslami, SUNY/Buffalo (United States)
Aidong Zhang, SUNY/Buffalo (United States)


Published in SPIE Proceedings Vol. 3017:
Visual Data Exploration and Analysis IV
Georges G. Grinstein; Robert F. Erbacher, Editor(s)

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