Abstract
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.
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References
Scrra, J., 1982, “Image Analysis and Mathematical Morphology”,Academic Press, New York.
Maragos, P., 1987, Pattern Spectrum of Images and Morphological Shape-Size Complexity, Proceedings of IEE. Int. Conf. on Acoustics, Speech and Signal Processing.
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.
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© 1989 Plenum Press, New York
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Binaghi, M., Cappellini, V., Raspollini, C. (1989). Multidimensional Discrete Signals Description Using Rotation and Scale Invariant Pattern Spectrum. In: Di Gesù, V., Scarsi, L., Crane, P., Friedman, J.H., Levialdi, S., Maccarone, M.C. (eds) Data Analysis in Astronomy III. Ettore Majorana International Science Series, vol 40. Springer, Boston, MA. https://doi.org/10.1007/978-1-4684-5646-2_9
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DOI: https://doi.org/10.1007/978-1-4684-5646-2_9
Publisher Name: Springer, Boston, MA
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Online ISBN: 978-1-4684-5646-2
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