Top-points as interest points for image matching

Bram Platel, Evguenia Balmachnova, Luc Florack, Bart M. ter Haar Romeny

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We consider the use of top-points for object retrieval. These points are based on scale-space and catastrophe theory, and are invariant under gray value scaling and offset as well as scale-Euclidean transformations. The differential properties and noise characteristics of these points are mathematically well understood. It is possible to retrieve the exact location of a top-point from any coarse estimation through a closed-form vector equation which only depends on local derivatives in the estimated point. All these properties make top-points highly suitable as anchor points for invariant matching schemes. By means of a set of repeatability experiments and receiver-operator-curves we demonstrate the performance of top-points and differential invariant features as image descriptors.
Original languageEnglish
Title of host publicationComputer Vision - ECCV 2006 (Proceedings 9th European Conference on Computer Vision, Graz, Austria, May 7-13, 2006)
EditorsH. Bischof, A. Leonardis, A. Pinz
Number of pages12
ISBN (Print)3-540-33832-2
Publication statusPublished - 2006

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743


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