Device Space Design for Efficient Scale-Space Edge Detection

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16 Citations (Scopus)

Abstract

We present a new approach to the computation of scalable image derivative operators, based on the finite element method, that addresses the issues of method, efficiency and scale-adaptability. The design procedure is applied to the problem of approximating scalable differential operators within the framework of Schwartz distributions. Within this framework, the finite element approach allows us to define a device space in which scalable image derivative operators are implemented using a combination of piecewise-polynomial and Gaussian basis functions.Here we illustrate the approach in relation to the problem of scale-space edge detection, in which significant scale-space edge points are identified by maxima of existing edge-strength measures that are based on combinations of scale-normalised derivatives. We partition the image in order to locally identify approximate ranges of scales within which significant edge points may exist, thereby avoiding unnecessary computation of edge-strength measures across the entire range of scales.
Original languageEnglish
Title of host publicationUnknown Host Publication
PublisherSpringer
Pages1077-1086
Number of pages10
VolumeLNCS 2
ISBN (Print)3-540-43594-8
DOIs
Publication statusPublished - Apr 2002
EventInternational Conference on Computational Science (ICCS 2002) - Amsterdam, The Netherlands
Duration: 1 Apr 2002 → …

Conference

ConferenceInternational Conference on Computational Science (ICCS 2002)
Period1/04/02 → …

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Keywords

  • device space design
  • scale space
  • edge detection
  • image derivative operators

Cite this

Scotney, BW., Coleman, SA., & Herron, MG. (2002). Device Space Design for Efficient Scale-Space Edge Detection. In Unknown Host Publication (Vol. LNCS 2, pp. 1077-1086). Springer. https://doi.org/10.1007/3-540-46043-8_109