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Proceedings Paper

World-Wide-Web-based image search engine using text and image content features
Author(s): Bo Luo; Xiaogang Wang; Xiaoou Tang
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Paper Abstract

Using both text and image content features, a hybrid image retrieval system for Word Wide Web is developed in this paper. We first use a text-based image meta-search engine to retrieve images from the Web based on the text information on the image host pages to provide an initial image set. Because of the high-speed and low cost nature of the text-based approach, we can easily retrieve a broad coverage of images with a high recall rate and a relatively low precision. An image content based ordering is then performed on the initial image set. All the images are clustered into different folders based on the image content features. In addition, the images can be re-ranked by the content features according to the user feedback. Such a design makes it truly practical to use both text and image content for image retrieval over the Internet. Experimental results confirm the efficiency of the system.

Paper Details

Date Published: 10 January 2003
PDF: 8 pages
Proc. SPIE 5018, Internet Imaging IV, (10 January 2003); doi: 10.1117/12.476329
Show Author Affiliations
Bo Luo, Chinese Univ. of Hong Kong (China)
Xiaogang Wang, Chinese Univ. of Hong Kong (China)
Xiaoou Tang, Chinese Univ. of Hong Kong (China)

Published in SPIE Proceedings Vol. 5018:
Internet Imaging IV
Simone Santini; Raimondo Schettini, Editor(s)

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