Cinbiş, R. GökberkAksoy, Selim2016-02-082016-02-082007-09-10http://hdl.handle.net/11693/26917Date of Conference: 16 Sept.-19 Oct. 2007Conference name: 2007 IEEE International Conference on Image ProcessingSpatial information is a crucial aspect of image understanding for modeling context as well as resolving the uncertainties caused by the ambiguities in low-level features. We describe intuitive, flexible and efficient methods for modeling pairwise directional spatial relationships and the ternary between relation using fuzzy mathematical morphology. First, a fuzzy landscape is constructed where each point is assigned a value that quantifies its relative position according to the reference object(s) and the type of the relationship. Then, the degree of satisfaction of this relation by a target object is computed by integrating the corresponding landscape over the support of the target region. Our models support sensitivity to visibility to handle areas that are partially enclosed by objects and are not visible from image points along the direction of interest. They can also cope with the cases where one object is significantly spatially extended relative to others. Experiments using synthetic and real images show that our models produce more intuitive results than other techniques. ©2007 IEEE.EnglishBetweenFuzzy setsMathematical morphologyRelative positionSpatial relationshipsDegree of satisfactionsEfficient methodsFuzzy mathematical morphologiesImage pointsReal imagesReference objectsRelative positionSpatial informationsSpatial relationshipsTarget objectsTarget regionsDigital image storageImage processingImaging systemsMorphologyConference Paper10.1109/ICIP.2007.4379101