ICIAP 1995: Image Analysis and Processing pp 405-410 | Cite as

A proposal on local and adaptive determination of filter scale for edge detection

  • Domenico G. Sorrenti
Low-level Image Processing
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 974)

Abstract

In this work a proposal about local and adaptive scale selection in edge detection is presented. Such a proposal follows Canny's optimality criterion, i.e., the smallest scale that provides a minimum value for the signal to noise ratio should be selected for each edge pixel. The proposal exploits a local regularity, i.e. SNR, measure that is based on a simplified version of the Kitchen-Rosenfeld edge quality evaluator. This measure makes possible a local definition of the scale. The work has been carried out with non-directional gaussian smoothing operators. The integration of the results, obtained at different scales on a pixel basis, into a single edge map is also tackled. Experimental work on real images is presented.

Keywords

Edge Detection Edge Direction Neighboring Pixel Coarse Scale Central Pixel 
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.
Download to read the full conference paper text

References

  1. [1]
    Rosenfeld A., Thurston M., “Edge and curve detection for visual scene analysis”, IEEE Trans. on Computers, May 1971Google Scholar
  2. [2]
    Witkin A. P., “Scale-space filtering”, Proc. Int. Joint Conf. Artificial Intelligence 1983Google Scholar
  3. [3]
    Canny J., “A computational approach to edge detection”, IEEE Trans. on PAMI, November 1986Google Scholar
  4. [4]
    Bergholm F., “Edge focusing”, IEEE Trans. on PAMI November 1987Google Scholar
  5. [5]
    Jeong H., Kim C. I., “Adaptive determination of filter scale for edge detection”, IEEE Trans. on PAMI, May 1992Google Scholar
  6. [6]
    Kitchen L., Rosenfeld A., “Edge evaluation using local edge coherence”, IEEE Trans. on SMC, September 1981Google Scholar
  7. [7]
    Perona P., Malik J., “Scale-space and edge detection using anisotropic diffusion”, IEEE Trans. on PAMI, July 1990Google Scholar
  8. [8]
    Deriche R., “Fast algorithms for low-level vision”, IEEE Trans. on PAMI, January 1990Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Domenico G. Sorrenti
    • 1
  1. 1.AI and Robotics Lab., Dept. Elettronica e InformazionePolitecnico di MilanoMilanoItaly

Personalised recommendations