Colour image filtering with component-graphs

Abstract : Mathematical morphology, initially devoted to binary and grey-level image processing, also offers opportunities to develop efficient tools for multivalued – and in particular, colour – images. In this context, connected operators are increasingly considered as a relevant way to obtain such tools, mainly for image filtering and segmentation purposes. In this article, we focus on connected operators based on component-trees and their extension to multivalued images, namely component-graphs. Beyond the classical colour-handling strategies, we show how component-graphs can be algorithmically used to efficiently handle the whole structural information gathered by colour spaces, in order to finally design original image filtering tools.
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https://hal.univ-reims.fr/hal-01695069
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Benoît Naegel, Nicolas Passat. Colour image filtering with component-graphs. International Conference on Pattern Recognition (ICPR), 2014, Stockholm, Sweden. pp.1621-1626, ⟨10.1109/ICPR.2014.287⟩. ⟨hal-01695069⟩

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