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Mathematical Morphology on Hypergraphs Using Vertex-Hyperedge Correspondence

DOI: 10.1155/2014/436419

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Abstract:

The focus of this paper is to develop computationally efficient mathematical morphology operators on hypergraphs. To this aim we consider lattice structures on hypergraphs on which we build morphological operators. We develop a pair of dual adjunctions between the vertex set and the hyperedge set of a hypergraph , by defining a vertex-hyperedge correspondence. This allows us to recover the classical notion of a dilation/erosion of a subset of vertices and to extend it to subhypergraphs of . This paper also studies the concept of morphological adjunction on hypergraphs for which both the input and the output are hypergraphs. 1. Introduction Mathematical morphology, appeared in 1960s, is a theory of nonlinear information processing [1–4]. It is a branch of image analysis based on algebraic, set-theoretic, and geometric principles [5, 6]. Originally, it is developed for binary images by Matheron and Serra. They are the first to observe that a general theory of mathematical morphology is based on the assumption that the underlying image space is a complete lattice. Most of the morphological theories at this abstract level were developed and presented without making references to the properties of the underlying space. Considering digital objects carrying structural information, mathematical morphology has been developed on graphs [7–10] and simplicial complexes [11], but little work has been done on hypergraphs [12–15]. When dealing with a hypergraph , we need to consider the hypergraph induced by the subset of vertices of (see Figures 1(a) and 1(b), where the blue vertices and edges in (b) represent ). We associate with the largest subset of hyperedges of such that the obtained pair is a hypergraph. We denote it by (see Section 3.1 and Figure 1(b)). We also consider a hypergraph induced by a subset of the edges of , namely, . Figure 1: Illustration of hypergraph dilation. Here we propose a systematic study of the basic operators that are used to derive a set of hyperedges from a set of vertices and a set of vertices from a set of hyperedges. These operators are the hypergraph extension to the operators defined by Cousty et al. [7, 8] for graphs. Since a hypergraph becomes a graph when for every hyperedge , all the properties of these operators are satisfied for graphs also. We emphasise that the input and output of these operators are both hypergraphs. The blue subhypergraph in Figure 1(c) is the result of the dilation of the blue subhypergraph in Figure 1(b) proposed in this paper. Here the resultant subhypergraph in Figure 1(c) is not induced by its

References

[1]  R. C. Gonzalez and E. Richard, Woods, Digital Image Processing, Prentice Hall Press, 2002.
[2]  J. P. Serra, Image Analysis and Mathematical Morphology, 1982.
[3]  M. Jourlin, B. Laget, G. Matheron et al., Image Analysis and Mathematical Morphology. Vol. 2: Theoretical Advances, 1988.
[4]  F. Y. Shih, Image Processing and Mathematical Morphology: Fundamentals and Applications, CRC Press, Boca Raton, Fla, USA, 2010.
[5]  H. J. A. M. Heijmans and C. Ronse, “The algebraic basis of mathematical morphology. I: dilations and erosions,” Computer Vision, Graphics, and Image Processing, vol. 50, no. 3, pp. 245–295, 1990.
[6]  C. Ronse, “Why mathematical morphology needs complete lattices,” Signal Processing, vol. 21, no. 2, pp. 129–154, 1990.
[7]  J. Cousty, L. Najman, F. Dias, and J. Serra, “Morphological filtering on graphs,” Computer Vision and Image Understanding, vol. 117, no. 4, pp. 370–385, 2013.
[8]  J. Cousty, L. Najman, and J. Serra, “Some morphological operators in graph spaces,” in Mathematical Morphology and Its Application to Signal and Image Processing, vol. 5720, pp. 149–160, Springer, Berlin, Germay, 2009.
[9]  H. Heijmans and L. Vincent, “Graph morphology in image analysis,” in Mathematical Morphology in Image Processing, vol. 34, pp. 171–203, Dekker, 1993.
[10]  L. Vincent, “Graphs and mathematical morphology,” Signal Processing, vol. 16, no. 4, pp. 365–388, 1989.
[11]  F. Dias, J. Cousty, and L. Najman, “Some morphological operators on simplicial complex spaces,” in Discrete Geometry for Computer Imagery, vol. 6607, pp. 441–452, Springer, 2011.
[12]  I. Bloch and A. Bretto, “Mathematical morphology on hypergraphs: preliminary definitions and results,” in Discrete Geometry for Computer Imagery, vol. 6607, pp. 429–440, Springer, 2011.
[13]  I. Bloch and A. Bretto, “Mathematical morphology on hypergraphsapplication to similarity and positive kernel,” Computer Vision and Image Understanding, vol. 117, no. 4, pp. 342–354, 2013.
[14]  I. Bloch, A. Bretto, and A. Leborgne, “Similarity between hypergraphs based on mathematical morphology,” in Mathematical Morphology and Its Applications to Signal and Image Processing, pp. 1–12, Springer, 2013.
[15]  J. G. Stell, “Relations on hypergraphs,” in Relational and Algebraic Methods in Computer Science, vol. 7560, pp. 326–341, Springer, 2012.
[16]  L. Najman and F. Meyer, “A short tour of mathematical morphology on edge and vertex weighted graphs,” in Image Processing and Analysis With Graphs: Theory and Practice, pp. 141–174, 2012.
[17]  A. Bretto, J. Azema, H. Cherifi, and B. Laget, “Combinatorics and image processing,” Graphical Models and Image Processing, vol. 59, no. 5, pp. 265–277, 1997.
[18]  C. Berge, Hypergraphs: Combinatorics of Finite Sets, vol. 45, North-Holland Publishing, Amsterdam, The Netherlands, 1989.
[19]  H. J. A. M. Heijmans, “Composing morphological filters,” IEEE Transactions on Image Processing, vol. 6, no. 5, pp. 713–723, 1997.

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