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Internal Report IIFLMB 01/98, AlbertLudwigsUniversit at Freiburg, Germany, January 1998 Local Invariant Feature Histograms
 

Summary: Internal Report IIF­LMB 01/98, Albert­Ludwigs­Universit¨ at Freiburg, Germany, January 1998
Local Invariant Feature Histograms
for Image Retrieval
S. Siggelkow, H. Burkhardt
Albert­Ludwigs­Universit¨ at Freiburg
Institut f¨ ur Informatik
79085 Freiburg i. Br., Germany
sven.siggelkow@informatik.uni­freiburg.de
Abstract
Among other techniques especially methods working fully automatically are of interest for
image retrieval from large data collections. Histograms proved successful in automatic im­
age retrieval, however their drawback is, that all structural information is lost. Therefore
we use histograms of features, that take into account the relations within a local neigh­
bourhood. These features are based on nonlinear functions (monomials). By integrating
over the Euclidean motion we extract features that are invariant with respect to transla­
tion and rotation. Thus we combine the advantage of an invariant description (e.g. we
only need one histogram for a whole class of transformed images in the database) with the
properties of histogram approaches, providing the possibility to find images also by partial
views or vice versa or to detect objects also under occlusion. Furthermore we removed the
disadvantage of classic histograms, their unsteady assignment at the bin boundaries, by

  

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

 

Collections: Computer Technologies and Information Sciences