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Transitions of Multi-scale Singularity Trees

  • Kerawit Somchaipeng
  • Jon Sporring
  • Sven Kreiborg
  • Peter Johansen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3753)

Abstract

Multi-Scale Singularity Trees(MSSTs) [10] are multi-scale image descriptors aimed at representing the deep structures of images. Changes in images are directly translated to changes in the deep structures; therefore transitions in MSSTs. Because MSSTs can be used to represent the deep structure of images efficiently, it is important to investigate and understand their transitions and impacts. We present four kinds of MSST transitions and discuss the potential advantages of Saddle-Based MSSTs over Extrema-Based MSSTs. The study of MSST transitions presented in this paper is an important step towards the development of the image matching and indexing algorithms based on MSSTs.

Keywords

Critical Path Deep Structure Image Segment Saddle Path Extremal Path 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Kerawit Somchaipeng
    • 1
    • 2
  • Jon Sporring
    • 2
  • Sven Kreiborg
    • 1
  • Peter Johansen
    • 2
  1. 1.3D-Lab, School of Dentistry, Dept. of Pediatric DentistryUniversity of CopenhagenCopenhagen NDenmark
  2. 2.Dept. of Computer ScienceUniversity of CopenhagenCopenhagen NDenmark

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