Query by image example: the comparison algorithm for navigating digital image databases (CANDID) approach

Patrick M. Kelly; T. Michael Cannon; Donald R. Hush

doi:10.1117/12.205289

23 March 1995 Query by image example: the comparison algorithm for navigating digital image databases (CANDID) approach

Patrick M. Kelly, T. Michael Cannon, Donald R. Hush

Proceedings Volume 2420, Storage and Retrieval for Image and Video Databases III; (1995) https://doi.org/10.1117/12.205289
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1995, San Jose, CA, United States

Abstract

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, we present CANDID and highlight two results from our 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.

Citation Download Citation

Patrick M. Kelly, T. Michael Cannon, and Donald R. Hush "Query by image example: the comparison algorithm for navigating digital image databases (CANDID) approach", Proc. SPIE 2420, Storage and Retrieval for Image and Video Databases III, (23 March 1995); https://doi.org/10.1117/12.205289

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