Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/40739
Title: Image categorization based on clustering spatial frequency maps
Authors: Long, F
Peng, H
Feng, D
Keywords: Spatial frequencies
Databases
Image classification
Issue Date: 2004
Publisher: SPIE-International Society for Optical Engineering
Source: Proceedings of SPIE : the International Society for Optical Engineering, 2004, v. 5307, 212 How to cite?
Journal: Proceedings of SPIE : the International Society for Optical Engineering 
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.
Description: Conference on Storage and Retrieval Methods and Applications for Multimedia 2004, San Jose, U.S.A., January 2004
URI: http://hdl.handle.net/10397/40739
ISSN: 0277-786X
EISSN: 1996-756X
DOI: 10.1117/12.527284
Appears in Collections:Conference Paper

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