DocumentCode
2342593
Title
Elastic Shape Registration Using an Incremental Free Form Deformation Approach with the ICP Algorithm
Author
Abdelmunim, Hossam ; Farag, Aly A.
Author_Institution
Comput. & Syst. Eng. Dept., Ain Shams Univ., Cairo, Egypt
fYear
2011
fDate
25-27 May 2011
Firstpage
212
Lastpage
218
Abstract
Shape registration is one of the most challenging problems in computer vision and medical imaging. The process is affected by the way the shape is represented and the form of transformation used to move the source shape. Our paper handles the elastic shape registration by combining the incremental free form deformation (IFFD) with the point-based registration technique using the sum of least squares method. The iterative closest point (ICP) algorithm is used as a criteria to establish point correspondences in each level of the IFFD framework. The free form deformation (FFD) is well known in the literature and works by forming a lattice of control points that can move and hence deform the domain grid points smoothly and uniformly under some shape constrains. The control lattice resolution is increased step by step to achieve a satisfactory deformation of the source shape to exactly match the target boundaries. Our point-based registration is based on least squares that measure the Euclidean distance between source and target boundaries in addition to the shape constrains. The minimization gives a closed form solution of the lattice control points positions. Promising results will be demonstrated for closed and open shapes and structures. The approach can also work for structures that contain multiple parts without any problems.
Keywords
image registration; iterative methods; least squares approximations; shape recognition; Euclidean distance; FFD; ICP; ICP algorithm; IFFD; closed shapes; computer vision; elastic shape registration; incremental free form deformation approach; iterative closest point; lattice resolution; least squares method; medical imaging; open shapes; point based registration; point based registration technique; shape constrains; source shape; target boundaries; Energy resolution; Equations; Image resolution; Iterative closest point algorithm; Lattices; Mathematical model; Shape; Anatomical Structures; ICP Algorithm; Shape Registration; Shape Representation;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Robot Vision (CRV), 2011 Canadian Conference on
Conference_Location
St. Johns, NL
Print_ISBN
978-1-61284-430-5
Electronic_ISBN
978-0-7695-4362-8
Type
conf
DOI
10.1109/CRV.2011.35
Filename
5957563
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