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Titlebook: Mathematical Morphology: 40 Years On; Proceedings of the 7 Christian Ronse,Laurent Najman,Etienne Decencière Conference proceedings 2005 Sp

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楼主: Debilitate
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Numerical Residuessociated functions. Two of these numerical residues will be introduced, called respectively ultimate opening and quasi-distance and, through some applications, the interest and efficiency of these operators will be illustrated.
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Grayscale Level Multiconnectivity. We show that grayscale level multiconnectivity defines a connection, provided that the connectivities used for the threshold sets obey a nesting condition. Multiconnected grayscale reconstruction is illustrated with an example of scale-space representation.
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Morphological Segmentations of Colour Imagesnance histograms. It yields partial, but instructive results which suggest a model for the distribution of the light over the space. Second, the combination of luminance dominant and hue dominant regions in images. Third, the synthesis between colour and shape information in human bust tracking.
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Second-Order Connected Attribute Filters Using Max-Trees is shaped by the component hierarchy of the modified image while the node attributes are based on the connected components of the original image. Attribute filtering of second-order connected sets proceeds as in conventional Max-Trees with no further computational overhead.
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Attribute-Space Connected Filters can be defined under certain conditions, and pattern spectra in most cases. The advantage of this approach is that regions can be split into constituent parts before filtering more naturally than by using partitioning connectivities.
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Ruminations on Tarjan’s Union-Find Algorithm and Connected Operatorss. In particular, we give clues to handle correctly the constraint of domain-disjointness preservation and, as a consequence, we show how we can rely on “union-find” to obtain algorithms for self-dual filters approaches and levelings with a marker function.
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Watershed-Driven Region-Based Image Retrievalthm that extracts automatically meaningful regions. In this framework, the proposed robust feature extraction plays a major role along with a novel region weighting for enhancing feature discrimination. Experimental results demonstrate the performance of the proposed strategy.
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