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Proceedings Paper

Content-based retrieval applied to drawing-image databases
Author(s): Koji Wakimoto; Mitsuhide Shima; Satoshi Tanaka; Akira Maeda
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Paper Abstract

In this paper, a method of image information retrieval is presented. The method employs a new similarity measure between graph representations of images. The measure is effective for drawing images that describe logical meaning by their structure. Most of the currently available image database systems offer retrieval functions called key word retrieval, where users specify key words such as titles, attributes, and categories of themes. But it is not easy for the users to select suitable key words according to the purpose of retrieval. So recently some retrieval functions called similarity retrieval have been proposed, where users specify key images by means of examples, sketches, and icons. We are developing a drawing image database system that stores plant diagrams. The system scans, recognizes, and stores plant diagrams. Then users can refer to any parts of the diagrams according to their needs. The system is used as a help to plant observation and control. To realize similarity retrieval for logically structured drawings like plant diagrams, we introduced a graph representation of drawings, which is suitable to deal with their logical structure. Then we defined a similarity measure between them. In this paper, effectiveness of the similarity measure and applicability to plant diagrams are discussed and some experimental results are shown.

Paper Details

Date Published: 14 April 1993
PDF: 11 pages
Proc. SPIE 1908, Storage and Retrieval for Image and Video Databases, (14 April 1993); doi: 10.1117/12.143657
Show Author Affiliations
Koji Wakimoto, Mitsubishi Electric Corp. (Japan)
Mitsuhide Shima, Mitsubishi Electric Corp. (Japan)
Satoshi Tanaka, Mitsubishi Electric Corp. (Japan)
Akira Maeda, Mitsubishi Electric Corp. (Japan)

Published in SPIE Proceedings Vol. 1908:
Storage and Retrieval for Image and Video Databases
Carlton Wayne Niblack, Editor(s)

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