1998
@phdthesis{Dim1998,
vgclass = {thesis},
vgproject = {cbir},
author = {Alexander Dimai},
title = {Scene Configuration Based Preattentive Similarity
Assessments for Content Based Image Retrieval},
school = {Communications Technology Laboratory, Swiss Federal
Institute of Technology, ETH},
address = {CH-8092 Z\"{u}rich, Switzerland},
month = {February},
year = {1998},
abstract = {This thesis addresses content based image retrieval, an
important topic in information management. The rapid expansion of
computer networks and the dramatically falling cost of data storage are
making image databases increasingly common. The growth in number and
size of image databases creates the need for new methods to access and
to search images. Conventional database search is based on textual
queries and provides only a partial solution to the problem, because
perceptual cues contained in an image are not fully exploited.
Consequently, the ultimate goal is to find image descriptors capturing
perceptual information of an image and allowing similarity assessments
between image scenes with a sophistication and versatility comparable
to that of human.
My thesis asserts that scene configuration based image descriptors and
a non-linear comparison scheme indexes robustly and effectively
preattentive contents of images. For supporting this thesis, this
dissertation inquires into three components: 1) \emph{evaluation
method}, 2) \emph{descriptor extraction}, and 3) \emph{comparison
scheme}. \ldots},
}