Similarity measures for image databases

Ramesh C. Jain, S. N. Murthy, Luong Tran, Shankar Chatterjee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

33 Scopus citations


Similarity between images is used for storage and retrieval in image databases. In the literature, several similarity measures have been proposed that may be broadly categorized as: (1) metric based, (2) set-theoretic based, and (3) decision-theoretic based measures. In each category, measured based on crisp logic as well as fuzzy logic are available. In some applications such as image databases, measures based on fuzzy logic would appear to be naturally better suited, although so far no comprehensive experimental study has been undertaken. In this paper, we report results of some of the experiments designed to compare various similarity measures for application to image databases. We are currently working with texture images and intend to work with face images in the near future. As a first step for comparison, the similarity matrices for each of the similarity measures are computed over a set of selected textures and are presented as visual images. Comparative analysis of these images reveals the relative characteristics of each of these measures. Further experiments are needed to study their sensitivity to small changes in images such as illumination, magnification, orientation, etc. We describe these experiments (sensitivity analysis, transition analysis, etc.) that are currently in progress. The results from these experiments offer assistance in choosing the appropriate measure for applications to image databases.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherSociety of Photo-Optical Instrumentation Engineers
Number of pages8
ISBN (Print)081941767X, 9780819417671
StatePublished - 1995
EventStorage and Retrieval for Image and Video Databases III - San Jose, CA, USA
Duration: Feb 9 1995Feb 10 1995


ConferenceStorage and Retrieval for Image and Video Databases III
CitySan Jose, CA, USA


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