2002
@article{CBG2002,
vgclass = {refpap},
vgproject = {cbir},
author = {Chad Carson and Serge Belongie and Hayit Greenspan and Jitendra Malik},
title = {Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {24},
number = {8},
pages = {1026--1038},
month = {August},
year = {2002},
url = {http://www.computer.org/tpami/tp2002/i1026abs.htm},
url1 = {http://ieeexplore.ieee.org/iel5/34/22016/01023800.pdf},
abstract = {Retrieving images from large and varied collections using
image content as a key is a challenging and important problem. We
present a new image representation that provides a transformation from
the raw pixel data to a small set of image regions that are coherent in
color and texture. This "Blobworld" representation is created by
clustering pixels in a joint color-texture-position feature space. The
segmentation algorithm is fully automatic and has been run on a
collection of 10,000 natural images. We describe a system that uses the
Blobworld representation to retrieve images from this collection. An
important aspect of the system is that the user is allowed to view the
internal representation of the submitted image and the query results.
Similar systems do not offer the user this view into the workings of
the system; consequently, query results from these systems can be
inexplicable, despite the availability of knobs for adjusting the
similarity metrics. By finding image regions that roughly correspond to
objects, we allow querying at the level of objects rather than global
image properties. We present results indicating that querying for
images using Blobworld produces higher precision than does querying
using color and texture histograms of the entire image in cases where
the image contains distinctive objects.},
}