Query by image example: The CANDID approach
Patrick Kelly, Michael Cannon, Donald R. Hush · University of North Texas Digital Library (University of North Texas) · 1995
CANDID (Comparison Algorithm for Navigating Digital Image Databases) was developed to enable contentbased 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 ever...