Stochastic Morphological Filtering and Bellman-Maslov Chains

Abstract : This paper introduces a probabilistic framework for adaptive morphological dilation and erosion. More precisely our probabilistic formalization is based on using random walk simulations for a stochastic estimation of adaptive and robust morphological operators. Hence, we propose a theoretically sound morphological counterpart of Monte Carlo stochastic filtering. The approach by simulations is inefficient but particularly tailorable for introducing different kinds of adaptability. From a theoretical viewpoint, stochastic morphological operators fit into the framework of Bellman-Maslov chains, the ( max , + )-counterpart of Markov chains, which the basis behind the efficient implementations using sparse matrix products.
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Communication dans un congrès
Cris L. Luengo Hendriks, Gunilla Borgefors, and Robin Strand. 11th International Symposium, ISMM 2013, May 2013, Uppsala, Sweden. Springer, 7883, pp.171-182, 2013, Lecture Notes in Computer Science. 〈10.1007/978-3-642-38294-9_15〉
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https://hal-mines-paristech.archives-ouvertes.fr/hal-00834635
Contributeur : Doriane Ibarra <>
Soumis le : lundi 17 juin 2013 - 09:10:05
Dernière modification le : mercredi 13 septembre 2017 - 01:03:01

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Jesus Angulo, Santiago Velasco-Forero. Stochastic Morphological Filtering and Bellman-Maslov Chains. Cris L. Luengo Hendriks, Gunilla Borgefors, and Robin Strand. 11th International Symposium, ISMM 2013, May 2013, Uppsala, Sweden. Springer, 7883, pp.171-182, 2013, Lecture Notes in Computer Science. 〈10.1007/978-3-642-38294-9_15〉. 〈hal-00834635〉

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