HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Conference papers

On Some Associations Between Mathematical Morphology and Artificial Intelligence

Abstract : This paper aims at providing an overview of the use of mathematical morphology, in its algebraic setting, in several fields of artificial intelligence (AI). Three domains of AI will be covered. In the first domain, mathematical morphology operators will be expressed in some logics (propositional, modal, description logics) to answer typical questions in knowledge representation and reasoning, such as revision, fusion, explanatory relations, satisfying usual postulates. In the second domain, spatial reasoning will benefit from spatial relations modeled using fuzzy sets and morphological operators, with applications in model-based image understanding. In the third domain, interactions between mathematical morphology and deep learning will be detailed. Morphological neural networks were introduced as an alternative to classical architectures, yielding a new geometry in decision surfaces. Deep networks were also trained to learn morphological operators and pipelines, and morphological algorithms were used as companion tools to machine learning, for pre/post processing or even regularization purposes. These ideas have known a large resurgence in the last few years and new ones are emerging.
Complete list of metadata

Contributor : Samy Blusseau Connect in order to contact the contributor
Submitted on : Wednesday, May 26, 2021 - 6:01:09 PM
Last modification on : Tuesday, January 4, 2022 - 5:50:45 AM
Long-term archiving on: : Friday, August 27, 2021 - 8:43:00 PM


Files produced by the author(s)



Isabelle Bloch, Samy Blusseau, Ramón Pino Pérez, Élodie Puybareau, Guillaume Tochon. On Some Associations Between Mathematical Morphology and Artificial Intelligence. DGMM 2021: Discrete Geometry and Mathematical Morphology, May 2021, Uppsala, Sweden. pp.457-469, ⟨10.1007/978-3-030-76657-3_33⟩. ⟨hal-03237697⟩



Record views


Files downloads