Multidimensional Discrete Signals Description Using Rotation and Scale Invariant Pattern Spectrum

  • M. Binaghi
  • V. Cappellini
  • C. Raspollini
Part of the Ettore Majorana International Science Series book series (EMISS, volume 40)


Mathematical morphology was developed in the mid 1960’s by G.Matheron and J.Serra as a methodology for continuous and discrete multidimensional signal analysis. The basic idea underlaying this methodology is to trasform the original signal into a simpler and more expressive one, by interacting with a structuring element, called kernel, strategically chosen by the observer. A morphological operation is then constitucd by a transformation followed by some measurement on the transformed signal. The measurement on the transformed signal can be its lenght, area, volume, etc., depending on the dimension of the signal.


Shape Description Mathematical Morphology Morphological Operation Minimum Euclidean Distance Pattern Spectrum 
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  2. Maragos, P., 1987, Pattern Spectrum of Images and Morphological Shape-Size Complexity, Proceedings of IEE. Int. Conf. on Acoustics, Speech and Signal Processing.Google Scholar
  3. Bronskill, J.F., and Venetsanopoulos, A.N., 1987 Multidimensional Shape Recognition using Mathematical Morphology, im “Time-Varying Image Processing and Moving Object Recognition”,V. Cappellini, ed., North-Holland, Amsterdam.Google Scholar

Copyright information

© Plenum Press, New York 1989

Authors and Affiliations

  • M. Binaghi
    • 1
  • V. Cappellini
    • 2
  • C. Raspollini
    • 3
  1. 1.Dipartimento di Ingegneria ElettronicaUniversity of FirenzeFirenzeItaly
  2. 2.Dipartimento di Ingegneria ElettronicaUniversity of Firenze and IROE -C.N.R.FirenzeItaly
  3. 3.IBM Rome Scientific CenterRomaItaly

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