2004
@article{GFS2004,
vgclass = {refpap},
vgproject = {cbir},
author = {Theo Gevers and Graham Finlayson and Raimondo Schettini},
title = {Color for Image Indexing and Retrieval},
journal = {Computer Vision and Image Understanding (special issue on Colour for Image Indexing and Retrieval)},
volume = {94},
number = {1--3},
pages = {1--2},
month = {April/June},
year = {2004},
note = {(Editorial Introduction)},
url = {http://dx.doi.org/10.1016/j.cviu.2004.03.001},
abstract = {There has been an enormous increase in the amount of
multimedia information used in various communication frameworks such as
education, entertainment, and news. Visual information (images and
video) is one of the most promising sources of multimedia information,
as it plays a key role in these communication frameworks. In fact, it
will be the most natural form of communication for new technologies
such as the Internet and mobile phones. This massive stimulus of the
exploitation of visual information creates demands for advanced storage
and retrieval technology for the management of large-scale image
assets. In fact, visual data management is not only necessary but also
essential for both society (e.g., news, e-education, and e-government)
and economy (e.g., content owners).
Although image data is the most natural data form in communication, it
is not easy to access, as the semantics of an image are not easily
deduced by a computer. To facilitate the extraction of these semantics,
color has become a center of interest. The interest in color is due
mainly to its superior discriminating power compared to gray-value
information. Further, color provides powerful information for image
data analysis, recognition, and visualization.
This special issue is aimed at the dissemination of contributions in
the area of color utilization in the exploration and visualization of
image data repositories for the purpose of content-based image access
\ldots},
}