Abstract
Filtering by morphological operations is particularly suited for removing clutter and noise objects which have been introduced into noiseless binary images containing shapes of interest. Morphological filtering is designed to exploit differences in the spatial nature (shape, size, orientation) of the objects (connected components) in the ideal noiseless images as compared to the noise/clutter objects. Since the typical noise models (union, intersection set difference, etc.) for binary images are not additive, the morphological processing is strongly nonlinear, optimal filtering results conventionally available for linear processing in the presence of additive noise are not directly applicable to morphological filtering of binary images. After morphological filtering for clutter reduction recognition can begin.
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© 1992 Springer Science+Business Media New York
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Haralick, R.M. (1992). Model-Based Morphology: Simple and Complex Shapes. In: Arcelli, C., Cordella, L.P., di Baja, G.S. (eds) Visual Form. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-0715-8_27
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DOI: https://doi.org/10.1007/978-1-4899-0715-8_27
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