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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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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creator Morales, J.
Verdu, R.
Berenguer, R.
Weruaga, L.
description 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_str_mv 10.1109/ICDSP.2002.1028151
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Biomedical imaging
Cost function
Fuzzy sets
Image matching
Image processing
Interpolation
Motion estimation
Parametric statistics
Phase estimation
Pixel
title Non-rigid motion estimation based on fuzzy models
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