Non-rigid motion estimation based on fuzzy models

Image matching of deformable structures has captured great attention in image processing, and specially in the medical field. This paper proposes a method that faces the ill-posed nature of this problem, by using a cluster-sized similarity cost function, the ambiguity in each similarity map is descr...

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Bibliographic Details
Main Authors: Morales, J., Verdu, R., Berenguer, R., Weruaga, L.
Format: Conference Proceeding
Language:English
Subjects:
Biomedical imaging
Cost function
Fuzzy sets
Image matching
Image processing
Interpolation
Motion estimation
Parametric statistics
Phase estimation
Pixel
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Summary:Image matching of deformable structures has captured great attention in image processing, and specially in the medical field. This paper proposes a method that faces the ill-posed nature of this problem, by using a cluster-sized similarity cost function, the ambiguity in each similarity map is described by a fuzzy parametric model, and, finally, a spatially non-uniform fuzzy interpolation is used to translate the parametric information into a set of matching field vectors. The method obtains the spatial matching between the two images in a global spatial extent and with sub-pixel accuracy. Results of the method on real images and high non-rigid artificial deformation proves the validity of the approach. Its extension to a volumetric approach is also suggested.
DOI:10.1109/ICDSP.2002.1028151