Summary: Noblesse Workshop on Non­Linear Model Based Image Analysis, Glasgow, July 1998
Image retrieval based on colour and
nonlinear texture invariants
Sven Siggelkow, Hans Burkhardt
Institute of Computer Science, Albert­Ludwigs­Universit¨at Freiburg
Freiburg, Germany
Abstract
Among other techniques especially methods working fully automatically
are of interest for image retrieval from large databases. Colour histograms
proved to be successful in automatic image retrieval, however, their draw­
back is that all structural information is lost. Therefore we extend the
colour histogram approach by features that take into account the relations
within a local pixel neighbourhood. By integrating nonlinear functions
over the group of Euclidean motion we extract features that are invariant
with respect to translation and rotation. In contrast to approaches using
linear filtering (e.g. wavelets) or corresponding power spectra (to become
invariant) these nonlinear invariants have the potential to be unique with
respect to the equivalence class of Euclidean motion. So in invariant fea­
ture histograms we combine the advantage of an invariant description
(e.g. we only need one histogram for a whole class of transformed images

Source: Albert-Ludwigs-Universität Freiburg, Institut für Informatik,, Lehrstuhls für Mustererkennung und Bildverarbeitung

Collections: Computer Technologies and Information Sciences