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Using Top-Points as Interest Points for Image Matching

  • Conference paper
Deep Structure, Singularities, and Computer Vision (DSSCV 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3753))

Abstract

We consider the use of so-called 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. In a set of examples we show the excellent performance of top-points in an object retrieval task.

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© 2005 Springer-Verlag Berlin Heidelberg

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Platel, B., Balmachnova, E., Florack, L.M.J., Kanters, F.M.W., ter Haar Romeny, B.M. (2005). Using Top-Points as Interest Points for Image Matching. In: Fogh Olsen, O., Florack, L., Kuijper, A. (eds) Deep Structure, Singularities, and Computer Vision. DSSCV 2005. Lecture Notes in Computer Science, vol 3753. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11577812_19

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  • DOI: https://doi.org/10.1007/11577812_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29836-6

  • Online ISBN: 978-3-540-32097-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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