FESID: Finite Element Scale Invariant Detector

  • Dermot Kerr
  • Sonya Coleman
  • Bryan Scotney
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5716)


Recently, finite element based methods have been used to develop gradient operators for edge detection that have improved angular accuracy over standard techniques. A more prominent issue in the field of image processing has become the use of interest point detectors and to this end we expand upon this research developing a finite element scale invariant interest point detector that is based on the same multi-scale approach used in the SURF detector. The operator differs in that the autocorrelation matrix is used to select the interest point location and the derivative and smoothing operations are combined into one operator developed through the use of the finite element framework.


Interest Point Integral Image Multiscale Approach Interest Point Detector Scale Selection 
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 2009

Authors and Affiliations

  • Dermot Kerr
    • 1
  • Sonya Coleman
    • 1
  • Bryan Scotney
    • 2
  1. 1.School of Computing and Intelligent SystemsUniversity of UlsterMageeNorthern Ireland
  2. 2.School of Computing and Information EngineeringUniversity of UlsterColeraineNorthern Ireland

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