DocumentCode :
2511246
Title :
Estimating Nonrigid Shape Deformation Using Moments
Author :
Liu, Wei ; Ribeiro, Eraldo
Author_Institution :
Comput. Vision & Bio-Inspired Comput. Lab., Florida Inst. of Technol., Melbourne, FL, USA
fYear :
2010
fDate :
23-26 Aug. 2010
Firstpage :
185
Lastpage :
188
Abstract :
Image moments have been widely used for designing robust shape descriptors that are invariant to rigid transformations. In this work, we address the problem of estimating non-rigid deformation fields based on image moment variations. By using a single family of polynomials to both parameterize the deformation field and to define image moments, we can represent image moments variation as a system of quadratic functions, and solve for the deformation parameters. As a result, we can recover the deformation field between two images without solving the correspondence problem. Additionally, our method is highly robust to image noise. The method was tested on both synthetically deformed MPEG-7 shapes and cardiac MRI sequences.
Keywords :
estimation theory; image representation; polynomials; shape recognition; MPEG-7 shapes; cardiac MRI sequences; deformation parameters; image moment variations; image moments; image noise; image representation; nonrigid shape deformation estimation; polynomials; quadratic functions; rigid transformations; robust shape descriptors; Deformable models; Magnetic resonance imaging; Mathematical model; Noise; Polynomials; Shape; moments; nonrigid deformation; nonrigid image registration; polynomials;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
ISSN :
1051-4651
Print_ISBN :
978-1-4244-7542-1
Type :
conf
DOI :
10.1109/ICPR.2010.54
Filename :
5597599
Link To Document :
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