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Proceedings Paper

Image/text automatic indexing and retrieval system using context vector approach
Author(s): Kent Pu Qing; William R. Caid; Clara Z. Ren; Patrick McCabe
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Paper Abstract

Thousands of documents and images are generated daily both on and off line on the information superhighway and other media. Storage technology has improved rapidly to handle these data but indexing this information is becoming very costly. HNC Software Inc. has developed a technology for automatic indexing and retrieval of free text and images. This technique is demonstrated and is based on the concept of `context vectors' which encode a succinct representation of the associated text and features of sub-image. In this paper, we will describe the Automated Librarian System which was designed for free text indexing and the Image Content Addressable Retrieval System (ICARS) which extends the technique from the text domain into the image domain. Both systems have the ability to automatically assign indices for a new document and/or image based on the content similarities in the database. ICARS also has the capability to retrieve images based on similarity of content using index terms, text description, and user-generated images as a query without performing segmentation or object recognition.

Paper Details

Date Published: 21 November 1995
PDF: 8 pages
Proc. SPIE 2606, Digital Image Storage and Archiving Systems, (21 November 1995); doi: 10.1117/12.227259
Show Author Affiliations
Kent Pu Qing, HNC Software Inc. (United States)
William R. Caid, HNC Software Inc. (United States)
Clara Z. Ren, HNC Software Inc. (United States)
Patrick McCabe, Rome Lab. (United States)


Published in SPIE Proceedings Vol. 2606:
Digital Image Storage and Archiving Systems
C.-C. Jay Kuo, Editor(s)

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