Toward a Recommendation System for Image Similarity Metrics
Peter Bajcsy, Joe Chalfoun, Mary C. Brady
This paper addresses the problem of mapping application specific requirements on image similarity metrics to the plethora of existing image similarity computations. The work is motivated by the fact that there is no recommendation method for choosing a similarity metric that is suitable for a given application. We approached the problem by designing a theoretical and experimental framework for creating sensitivity signatures of similarity metrics. In this paper, we outline the classifications of image similarity metrics found in literature, the space of application parameters and requirements, derivations of similarity dependencies on application parameters, and experimentally obtained sensitivity signatures of similarity metrics using image simulations. These sensitivity signatures provide a way for users to query a reference database of sensitivity signatures and retrieve a recommendation for an image similarity metric.
The International Association of Science and Technology for Development (IASTED)
May 14-16, 2012
The 2nd IASTED International Symposia on
Imaging and Signal Processing in Health Care and Technology,
, Chalfoun, J.
and Brady, M.
Toward a Recommendation System for Image Similarity Metrics, The International Association of Science and Technology for Development (IASTED), Baltimore, MD, [online], https://doi.org/10.1145/2382936.2383040
(Accessed November 30, 2023)