Fuzzy Sets and Systems - Special issue on fuzzy methods for computer vision and pattern recognition
Fuzzy aggregation of numerical preferences
Fuzzy sets in decision analysis, operations research and statistics
A New Way to Represent the Relative Position between Areal Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy Relative Position Between Objects in Image Processing: A Morphological Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Maintaining knowledge about temporal intervals
Communications of the ACM
Understanding the spatial organization of image regions by means of force histograms: a guided tour
Applying soft computing in defining spatial relations
Similarity of Cardinal Directions
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
R-Histogram: quantitative representation of spatial relations for similarity-based image retrieval
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Optimized polygonal approximation by dominant point deletion
Pattern Recognition
Fuzzy region connection calculus: An interpretation based on closeness
International Journal of Approximate Reasoning
Spatial Relations Analysis by Using Fuzzy Operators
ICCS 2009 Proceedings of the 9th International Conference on Computational Science
Imprecise temporal interval relations
WILF'05 Proceedings of the 6th international conference on Fuzzy Logic and Applications
Appropriate choice of aggregation operators in fuzzy decision support systems
IEEE Transactions on Fuzzy Systems
Combined topological and directional relations based motion event predictions
PReMI'11 Proceedings of the 4th international conference on Pattern recognition and machine intelligence
Two-dimensional fuzzy spatial relations: a new way of computing and representation
Advances in Fuzzy Systems
Spatio-temporal reasoning by combined topological and directional relations information
International Journal of Artificial Intelligence and Soft Computing
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Concept of combined extraction of topological and directional relations information developed by Zahzah et al. [1] by employing the Allen's temporal relations in 1D spatial domain was improved by Matsakis and Nikitenko [2]. This latter algorithm has high computational complexity due to its limitations of object approximation and segment fuzzification. In this paper, fuzzy Allen relations are used to define the fuzzy topological and directional relations information between different objects. Some extended results of Salamat and Zahzah [3] are discussed. Polygonal object approximation allows us to use fuzzy operators and this approach reduces computational complexity of the method for computing the combined topological and directional relations. To validate the method, some experiments are tested giving satisfactory and promising results. Affine transformation are depicted, these properties will be helpful for using the method in other areas of image analysis such as object tracking.