Top-Points as Interest Points for Image Matching

  • B. Platel
  • E. Balmachnova
  • L. M. J. Florack
  • B. M. ter Haar Romeny
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3951)


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.


Feature Vector Receiver Operating Characteristic Curve Critical Path Interest Point Query Image 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • B. Platel
    • 1
  • E. Balmachnova
    • 1
  • L. M. J. Florack
    • 1
  • B. M. ter Haar Romeny
    • 1
  1. 1.Technische Universiteit EindhovenEindhovenThe Netherlands

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