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Proceedings Paper

Categorizing images in web documents
Author(s): Jianying Hu; Amit Bagga
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Paper Abstract

The World Wide Web provides an increasingly powerful and popular publication mechanism. Web documents often contain a large number of images serving various different purposes. Identifying the functional categories of these images ahs important applications including information extraction, web mining, web page summarization and mobile access. An important first step towards designing algorithms for automatic categorization of images on the web is to identify the common categories and examine their properties and characteristics. This paper describes results from such an initial study using data collected from news web sites. We describe the image categories found in such web pages and their distributions, and identify the main research issues involved in automatically classifying images into these categories.

Paper Details

Date Published: 13 January 2003
PDF: 8 pages
Proc. SPIE 5010, Document Recognition and Retrieval X, (13 January 2003); doi: 10.1117/12.476059
Show Author Affiliations
Jianying Hu, Avaya Labs Research (United States)
Amit Bagga, Avaya Labs Research (United States)


Published in SPIE Proceedings Vol. 5010:
Document Recognition and Retrieval X
Tapas Kanungo; Elisa H. Barney Smith; Jianying Hu; Paul B. Kantor, Editor(s)

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