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Chabot: Retrieval from a Relational Database of Images
September 1995 (vol. 28 no. 9)
pp. 40-48
With its digitized image collection growing and the number of requests for prints and slides increasing, the State of California Department of Water Resources is looking to Chabot to enhance its search and retrieval capabilities. Chabot is a picture retrieval system for a database that will eventually include more than 500,000 digitized multiresolution images. The authors describe the design and construction of this system, which uses the relational database management system Postgres for storing and managing the images and their associated textual data. For retrieval, Chabot uses tools provided by Postgres, such as representation of complex data types, a rich query language, and extensible types and functions. To implement retrieval from the current collection of 11,643 images, Chabot integrates the use of stored text and other data types with content-based analysis of the images to perform "concept queries." As a first step toward integrating content analysis into the retrieval system, the authors implemented a method for image color analysis. They describe how the effectiveness of content analysis was tested by measuring the recall and precision obtained with certain concept queries. The use of either keywords or content alone failed to give satisfactory image retrieval results, but when concept queries combined both methods, results showed significant improvement.
Citation:
Virginia E. Ogle, Michael Stonebraker, "Chabot: Retrieval from a Relational Database of Images," Computer, vol. 28, no. 9, pp. 40-48, Sept. 1995, doi:10.1109/2.410150
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