By John Goutsias, Luc Vincent, Dan S. Bloomberg

Mathematical morphology is a strong technique for the processing and research of geometric constitution in signs and photographs. This booklet includes the complaints of the 5th foreign Symposium on *Mathematical Morphology and its functions to photo and Signal**Processing*, held June 26-28, 2000, at Xerox PARC, Palo Alto, California. It presents a large sampling of the latest theoretical and functional advancements of mathematical morphology and its purposes to picture and sign processing. components coated contain: decomposition of structuring capabilities and morphological operators, morphological discretization, filtering, connectivity and attached operators, morphological form research and interpolation, texture research, morphological segmentation, morphological multiresolution concepts and scale-spaces, and morphological algorithms and purposes. *Audience:* the subject material of this quantity could be of curiosity to electric engineers, desktop scientists, and mathematicians whose learn paintings is concentrated at the theoretical and sensible points of nonlinear sign and snapshot processing. it is going to even be of curiosity to these operating in laptop imaginative and prescient, utilized arithmetic, and laptop graphics.

**Read or Download Mathematical Morphology and its Applications to Image and Signal Processing PDF**

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**Sample text**

Remarks: Let F be a closed r-regular set in and let If ρ and P ∈ M , then all possible configurations at P are represented in Figure 3(b) (modulo a reflection and/or a 90° rotation). Corollary 1 Let F be a closed r-regular set in the set and let Then is a bordered 2D manifold. Theorem 6 Let d be a strictly homogeneous metric and K be a r-regular compact subset of such that K is a bordered 2D manifold. Let Then and K are homeomorphic. Let us mention related results from the literature: [17] showed that under certain conditions on a Euclidean set X, in the supercover discretization there are points that can be removed in such a way that for the remaining subset S of points, is homotopic to X.

Ronse. Hausdorff discretization and its comparison with other discretization schemes. DGCI’99, Paris, LNCS Springer-Verlag, Vol. 1568, pp. 399–410, 1999. 23. D. Wagner. Distance de Hausdorff et problème discret-continu. A. Sc. Dissertation), Université Louis Pasteur, Strasbourg (France), June 1997. gz 24. D. Wagner, M. Tajine and C. Ronse. An approach to discretization based on the Hausdorff metric. In H. Heijmans & J. Roerdink, editors, International Symposium on Mathematical Morphology 1998. Mathematical morphology and its applications to image and signal processing IV, pp.

In H. Heijmans & J. Roerdink, editors, International Symposium on Mathematical Morphology 1998. Mathematical morphology and its applications to image and signal processing IV, pp. 91–98, Kluwer Academic Publishers, June 1998. 18. J. Serra. Image analysis and mathematical morphology. Academic Press, London, 1982. 19. M. Tajine and C. Ronse. Preservation of topology by Hausdorff discretization and comparison to other discretization schemes. Submitted, 1999. 20. M. Tajine and C. Ronse. Hausdorff sampling of closed sets in a boundedly compact space.