Abstract
Morphological filters are an important class of non-linear digital signal processing and analysis filters, which have found a range of applications, giving excellent results in areas such as noise reduction, edge detection and object recognition. However, few design methods exist for these morphological filters, with selection of filter type and sequence of application tending to be both ad-hoc and application specific. This paper demonstrates how simple genetic algorithms can be employed in the search for optimum morphological filters for specific signal/image processing tasks.
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© 1994 Springer Science+Business Media Dordrecht
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Harvey, N.R., Marshall, S. (1994). Using Genetic Algorithms in the Design of Morphological Filters. In: Serra, J., Soille, P. (eds) Mathematical Morphology and Its Applications to Image Processing. Computational Imaging and Vision, vol 2. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-1040-2_8
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DOI: https://doi.org/10.1007/978-94-011-1040-2_8
Publisher Name: Springer, Dordrecht
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Online ISBN: 978-94-011-1040-2
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