Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences

COLLEGE OF ENGINEERING

UC Berkeley

Region-Based Image Querying

Serge Belongie, Chad Carson, Hayit Greenspan and Jitendra Malik

EECS Department
University of California, Berkeley
Technical Report No. UCB/CSD-97-941
April 1997

http://www.eecs.berkeley.edu/Pubs/TechRpts/1997/CSD-97-941.pdf

Retrieving images from large and varied collections using image content as a key is a challenging and important problem. In this paper we present an image representation which provides a transition from the raw pixel data to a small set of localized coherent regions in color and texture space. This so-called "blobworld" image description may be thought of as a summary representation which captures the basic compositional features of the image. An important and unique aspect of the system is that, in the context of similarity-based querying, the user is allowed to view the internal representation of the submitted image. Similar systems do not offer the user this view into the workings of the system; consequently the outcome of many queries on these systems can be quite inexplicable, despite the availability of knobs for adjusting the similarity metric.


BibTeX citation:

@techreport{Belongie:CSD-97-941,
    Author = {Belongie, Serge and Carson, Chad and Greenspan, Hayit and Malik, Jitendra},
    Title = {Region-Based Image Querying},
    Institution = {EECS Department, University of California, Berkeley},
    Year = {1997},
    Month = {Apr},
    URL = {http://www.eecs.berkeley.edu/Pubs/TechRpts/1997/5229.html},
    Number = {UCB/CSD-97-941},
    Abstract = {Retrieving images from large and varied collections using image content as a key is a challenging and important problem. In this paper we present an image representation which provides a transition from the raw pixel data to a small set of localized coherent regions in color and texture space. This so-called "blobworld" image description may be thought of as a summary representation which captures the basic compositional features of the image. An important and unique aspect of the system is that, in the context of similarity-based querying, the user is allowed to view the internal representation of the submitted image. Similar systems do not offer the user this view into the workings of the system; consequently the outcome of many queries on these systems can be quite inexplicable, despite the availability of knobs for adjusting the similarity metric.}
}

EndNote citation:

%0 Report
%A Belongie, Serge
%A Carson, Chad
%A Greenspan, Hayit
%A Malik, Jitendra
%T Region-Based Image Querying
%I EECS Department, University of California, Berkeley
%D 1997
%@ UCB/CSD-97-941
%U http://www.eecs.berkeley.edu/Pubs/TechRpts/1997/5229.html
%F Belongie:CSD-97-941