A New Extension of Linear Signal Processing for Estimating Local Properties and Detecting Features | SpringerLink
Skip to main content

A New Extension of Linear Signal Processing for Estimating Local Properties and Detecting Features

  • Conference paper
Mustererkennung 2000

Part of the book series: Informatik aktuell ((INFORMAT))

Abstract

The analytic signal is one of the most capable approaches in one-dimensional signal processing. Two-dimensional signal theory suffers from the absence of an isotropic extension of the analytic signal. Accepting the fact that there is no odd filter with isotropic energy in higher dimensions, one tried to circumvent this drawback using the one-dimensional quadrature Alters with respect to several preference directions. Disadvantages of these methods are an increased complexity, the loss of linearity and a lot of different heuristic approaches. In this paper we present a filter that is isotropic and odd, which means that the whole theory of local phase and amplitude can directly be applied to images. Additionally, a third local property is obtained which is the local orientation. The advantages of our approach are demonstrated by a stable orientation detection algorithm and an adaption of the phase congruency method which yields a superior edge detector with very low complexity.

This work has been supported by German National Merit Foundation and by DFG Graduiertenkolleg No. 357 (M. Felsberg) and by DFG So-320-2-2 (G. Sommer).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 5879
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 7349
Price includes VAT (Japan)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Brady, J.M., and Horn, B.M.P. Rotationally Symmetrie Operators for surface interpolation. Computer Vision, Graphics, and Image Processing 22, 1 (April 1983), 70–94.

    Article  MATH  Google Scholar 

  2. Canny, J. A computational approach to edge detection.IEEE Transactions on Pattern Analysis and Machine Intelligence 8, 6 (November 1986), 679–698.

    Article  Google Scholar 

  3. Felsberg, M., and Sommer, G. The multidimensional isotropic generalization of quadrature filters in geometric algebra. In Proc. Int. Workshop on Algebraic Frames for the Perception-Action Cycle, Kiel (2000), G. Sommer and Y. Zeevi, Eds., Lecture Notes in Computer Science, Springer-Verlag, Heidelberg, aeeepted.

    Google Scholar 

  4. Felsberg, M., and Sommer, G. Structure multivector for local analysis of images. Tech. Rep. 2001, Institute of Computer Science and Applied Mathematics, Christian-Albrechts-University of Kiel, Germany, February 2000.

    Google Scholar 

  5. Granlund, G.H. Hierarchical Computer vision. In Proc. of EUSIPCO-90, Fifth European Signal Processing Conference, Barcelona (1990), L. Torres, E. Masgrau, and M.A. Lagunas, Eds., pp. 73-84.

    Google Scholar 

  6. Granlund, G.H., and Knutsson, H. Signal Processing for Computer Vision. Kluwer Academic Publishers, Dordrecht, 1995.

    Google Scholar 

  7. Haglund, L. Adaptive Multidimensional Filtering. PhD thesis, Linköping University, 1992.

    Google Scholar 

  8. Hahn, S.L. Hilbert Transforms in Signal Processing. Artech House, Boston, London, 1996.

    MATH  Google Scholar 

  9. Jahne, B. Digitale Bildverarbeitung. Springer, Berlin, 1997.

    Google Scholar 

  10. Kovesi, P. Invariant Measures of Image Features from Phase Information. PhD thesis, University of Western Australia, 1996.

    Google Scholar 

  11. Kovesi, P. Image features from phase information. Videre: Journal of Computer Vision Research 1, 3 (1999).

    Google Scholar 

  12. Krieger, G., and Zetzsche, C. Nonlinear image operators for the evaluation of local intrinsic dimensionality. IEEE Transactions on Image Processing 5, 6 (June 1996), 1026–1041.

    Article  Google Scholar 

  13. Merron, J., and Brady, M. Isotropic gradient estimation. In IEEE Computer Vision and Pattern Recognition (1996), pp. 652-659.

    Google Scholar 

  14. Nabighian, M.N. Toward a three-dimensional automatic interpretation of Potential field data via generalized Hilbert transforms: Fundamental relations. Geophysics 49, 6 (June 1984), 780–786.

    Article  Google Scholar 

  15. Stein, E., and Weiss, G. Introduction to Fourier Analysis on Euclidean Spaces. Princeton University Press, New Jersey, 1971.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Felsberg, M., Sommer, G. (2000). A New Extension of Linear Signal Processing for Estimating Local Properties and Detecting Features. In: Sommer, G., Krüger, N., Perwass, C. (eds) Mustererkennung 2000. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59802-9_25

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-59802-9_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67886-1

  • Online ISBN: 978-3-642-59802-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics