Query by image example: The CANDID approach

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CANDID (Comparison Algorithm for Navigating Digital Image Databases) was developed to enable content-based retrieval of digital imagery from large databases using a query-by-example methodology. A user provides an example image to the system, and images in the database that are similar to that example are retrieved. The development of CANDID was inspired by the N-gram approach to document fingerprinting, where a ``global signature`` is computed for every document in a database and these signatures are compared to one another to determine the similarity between any two documents. CANDID computes a global signature for every image in a database, where the ... continued below

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12 p.

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Kelly, P.M.; Cannon, M. & Hush, D.R. February 1, 1995.

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  • Kelly, P.M.
  • Cannon, M. Los Alamos National Lab., NM (United States). Computer Research and Applications Group
  • Hush, D.R. Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Electrical and Computer Engineering

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Description

CANDID (Comparison Algorithm for Navigating Digital Image Databases) was developed to enable content-based retrieval of digital imagery from large databases using a query-by-example methodology. A user provides an example image to the system, and images in the database that are similar to that example are retrieved. The development of CANDID was inspired by the N-gram approach to document fingerprinting, where a ``global signature`` is computed for every document in a database and these signatures are compared to one another to determine the similarity between any two documents. CANDID computes a global signature for every image in a database, where the signature is derived from various image features such as localized texture, shape, or color information. A distance between probability density functions of feature vectors is then used to compare signatures. In this paper, the authors present CANDID and highlight two results from their current research: subtracting a ``background`` signature from every signature in a database in an attempt to improve system performance when using inner-product similarity measures, and visualizing the contribution of individual pixels in the matching process. These ideas are applicable to any histogram-based comparison technique.

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12 p.

Notes

OSTI as DE95006284

Source

  • SPIE `95: SPIE conference on optics, electro-optics, and laser application in science, engineering and medicine, San Jose, CA (United States), 5-14 Feb 1995

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  • Other: DE95006284
  • Report No.: LA-UR--95-374
  • Report No.: CONF-950226--12
  • Grant Number: W-7405-ENG-36
  • Office of Scientific & Technical Information Report Number: 28339
  • Archival Resource Key: ark:/67531/metadc668643

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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  • February 1, 1995

Added to The UNT Digital Library

  • June 29, 2015, 9:42 p.m.

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  • Feb. 26, 2016, 3:52 p.m.

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Kelly, P.M.; Cannon, M. & Hush, D.R. Query by image example: The CANDID approach, article, February 1, 1995; New Mexico. (digital.library.unt.edu/ark:/67531/metadc668643/: accessed December 12, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.