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Proceedings Paper

Image categorization based on clustering spatial frequency maps
Author(s): Fuhui Long; Hanchuan Peng; David Dagan Feng
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Paper Abstract

Image classification can facilitate semantic retrieval and browsing of large-scale image databases. Existing approaches are usually based on extracting local or global low-level features such as color, edge, and texture from images. In this paper, we propose an image categorization method that characterizes the respective scene structures in images. 2D Spatial Frequency Map of an image, as well as the respective projection vector representations and principal component representations, are used to characterize the spatial structure of the image. Based on multiple similarity scores, we use a spectral clustering method and a maximal-spanning-tree-spectral-clustering method to generate image categories.

Paper Details

Date Published: 18 December 2003
PDF: 11 pages
Proc. SPIE 5307, Storage and Retrieval Methods and Applications for Multimedia 2004, (18 December 2003); doi: 10.1117/12.527284
Show Author Affiliations
Fuhui Long, Duke Univ. (United States)
Hanchuan Peng, Oak Ridge National Lab. (United States)
David Dagan Feng, Hong Kong Polytechnic Univ. (China)
Univ. of Sydney (Australia)


Published in SPIE Proceedings Vol. 5307:
Storage and Retrieval Methods and Applications for Multimedia 2004
Minerva M. Yeung; Rainer W. Lienhart; Chung-Sheng Li, Editor(s)

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