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Steerable-scalable kernels for edge detection and junction analysis

  • Pietro Perona
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 588)

Abstract

Families of kernels that are useful in a variety of early vision algorithms may be obtained by rotating and scaling in a continuum a ‘template’ kernel. These multi-scale multi-orientation family may be approximated by linear interpolation of a discrete finite set of appropriate ‘basis’ kernels. A scheme for generating such a basis together with the appropriate interpolation weights is described. Unlike previous schemes by Perona, and Simoncelli et al. it is guaranteed to generate the most parsimonious one. Additionally, it is shown how to exploit two symmetries in edge-detection kernels for reducing storage and computational costs and generating simultaneously endstop- and junction-tuned filters for free.

Keywords

Singular Value Decomposition Edge Detection Discrete Fourier Transform Compact Operator Illusory Contour 
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 1992

Authors and Affiliations

  • Pietro Perona
    • 1
    • 2
  1. 1.California Institute of Technology 116-81PasadenaUSA
  2. 2.Università di Padova-DEIPadovaItaly

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