Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Fuzzy spatial relation ontology for image interpretation
Fuzzy Sets and Systems
Dilation and Erosion of Spatial Bipolar Fuzzy Sets
WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
Geometry of Spatial Bipolar Fuzzy Sets Based on Bipolar Fuzzy Numbers and Mathematical Morphology
WILF '09 Proceedings of the 8th International Workshop on Fuzzy Logic and Applications
Fuzzy spatial relationships for image processing and interpretation: a review
Image and Vision Computing
Duality vs adjunction and general form for fuzzy mathematical morphology
WILF'05 Proceedings of the 6th international conference on Fuzzy Logic and Applications
On the representation of intuitionistic fuzzy t-norms and t-conorms
IEEE Transactions on Fuzzy Systems
Integrating Bipolar Fuzzy Mathematical Morphology in Description Logics for Spatial Reasoning
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Lattices of fuzzy sets and bipolar fuzzy sets, and mathematical morphology
Information Sciences: an International Journal
Fuzzy bipolar mathematical morphology: a general algebraic setting
ISMM'11 Proceedings of the 10th international conference on Mathematical morphology and its applications to image and signal processing
Journal of Mathematical Imaging and Vision
Handling heterogeneous bipolar information for modelling environmental syndromes of global change
Environmental Modelling & Software
Mathematical morphology on bipolar fuzzy sets: general algebraic framework
International Journal of Approximate Reasoning
A t-norm embedding theorem for fuzzy sets
Fuzzy Sets and Systems
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Bipolarity is an important feature of spatial information, involved in the expressions of preferences and constraints about spatial positioning, or in pairs of "opposite" spatial relations such as left and right. Imprecision should also be taken into account, and fuzzy sets is then an appropriate formalism. In this paper, we propose to handle such information based on mathematical morphology operators, extended to the case of bipolar fuzzy sets. The potential of this formalism for spatial reasoning is illustrated on a simple example in brain imaging.