Relative position-based spatial relationships using mathematical morphology
Author
Cinbiş, R. Gökberk
Aksoy, Selim
Date
2007-09-10Source Title
Proceedings - International Conference on Image Processing, ICIP 2007
Publisher
IEEE
Pages
II-97 - II-100
Language
English
Type
Conference PaperItem Usage Stats
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Abstract
Spatial 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.
Keywords
BetweenFuzzy sets
Mathematical morphology
Relative position
Spatial relationships
Degree of satisfactions
Efficient methods
Fuzzy mathematical morphologies
Image points
Real images
Reference objects
Relative position
Spatial informations
Spatial relationships
Target objects
Target regions
Digital image storage
Image processing
Imaging systems
Morphology