Abstract
In this paper we present some remarks on dependence and similarity between morphological operations and other modern techniques of image treatment i.e. high-order neural networks, rough sets and fuzzy logic as well as its realization. Two basic morphological operations: erosion and dilation can be realized in many different ways including approaches based on precise mathematics of polynomial higher order neural nets (pi-sigma or functional link) or imprecise notions of uncertainty (fuzzy or rough sets). These concepts can be extended from binary images (sets) to gray level pictures (functions).
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Skoneczny, S., Stajniak, A., Szostakowski, J., Foltyniewicz, R. (1996). Links between Mathematical Morphology, Rough Sets, Fuzzy Logic and Higher Order Neural Networks. In: Maragos, P., Schafer, R.W., Butt, M.A. (eds) Mathematical Morphology and its Applications to Image and Signal Processing. Computational Imaging and Vision, vol 5. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-0469-2_20
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DOI: https://doi.org/10.1007/978-1-4613-0469-2_20
Publisher Name: Springer, Boston, MA
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