Abstract
In image analysis and pattern recognition fuzzy sets play the role of a good model for segmentation and classifications tasks when the regions and the classes cannot be strictly defined. Fuzzy morphology has been shown to be a very eficient tool in processing and segmentation of grey-scale images. In this work we show that using interval modelling we can apply efficiently fuzzy morphological operations to colour images. In this case intervals help us to avoid the problem of lack of total ordering in multidimensional Euclidean spaces, in particular in the three dimensional RGB colour space.
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Popov, A.T. (2007). Interval Based Morphological Colour Image Processing. In: Boyanov, T., Dimova, S., Georgiev, K., Nikolov, G. (eds) Numerical Methods and Applications. NMA 2006. Lecture Notes in Computer Science, vol 4310. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70942-8_40
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DOI: https://doi.org/10.1007/978-3-540-70942-8_40
Publisher Name: Springer, Berlin, Heidelberg
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