Toward a Recommendation System for Image Similarity Metrics

Published

October 7, 2012

Author(s)

Peter Bajcsy, Joe Chalfoun, Mary C. Brady

Abstract

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.

Proceedings Title

The International Association of Science and Technology for Development (IASTED)

Conference Dates

May 14-16, 2012

Conference Location

Baltimore, MD

Conference Title

The 2nd IASTED International Symposia on
Imaging and Signal Processing in Health Care and Technology,

Pub Type

Conferences

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DOI Link

Keywords

image similarity metrics, image comparison, recommendation system

Citation

Bajcsy, P. , Chalfoun, J. and Brady, M. (2012), 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 October 10, 2024)