Experience with CANDID: comparison algorithm for navigating digital image databases

Patrick M. Kelly; T. Michael Cannon

doi:10.1117/12.200807

31 January 1995 Experience with CANDID: comparison algorithm for navigating digital image databases

Patrick M. Kelly, T. Michael Cannon

Proceedings Volume 2368, 23rd AIPR Workshop: Image and Information Systems: Applications and Opportunities; (1995) https://doi.org/10.1117/12.200807
Event: 23 Annual AIPR Workshop: Image and Information Systems: Applications and Opportunities, 1994, Washington, DC, United States

Abstract

This paper presents results from our experience with CANDID (comparison algorithm for navigating digital image databases), which was designed to facilitate image retrieval by content using a query-by-example methodology. A global signature describing the texture, shape, or color content is first computed for every image stored in a database, and a normalized similarity measure between probability density functions of feature vectors is used to match signatures. This method can be used to retrieve images from a database that are similar to a user-provided example image. Results for three test applications are included.

Citation Download Citation

Patrick M. Kelly and T. Michael Cannon "Experience with CANDID: comparison algorithm for navigating digital image databases", Proc. SPIE 2368, 23rd AIPR Workshop: Image and Information Systems: Applications and Opportunities, (31 January 1995); https://doi.org/10.1117/12.200807

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