Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Boolean characterization of three-dimensional simple points
Pattern Recognition Letters
Skeleton-based three-dimensional geometric morphing
Computational Geometry: Theory and Applications - special issue on virtual reality
Digital Image Warping
3D/2D Registration via Skeletal Near Projective Invariance in Tubular Objects
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Integrated Approach for Matching Statistical Shape Models with Intra-operative 2D and 3D Data
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part II
2D and 3D visibility in discrete geometry: an application to discrete geodesic paths
Pattern Recognition Letters - Special issue: Discrete geometry for computer imagery (DGCI'2002)
Discrete average of two-dimensional shapes
CAIP'05 Proceedings of the 11th international conference on Computer Analysis of Images and Patterns
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In this article we present an algorithm for discrete object deformation. This algorithm is a first step for computing an average shape between two discrete objects and may be used for building a statistical atlas of shapes. The method we develop is based on discrete operators and works only on digital data. We do not compute continuous approximations of objects so that we have neither approximations nor interpolation errors. The first step of our method performs a rigid transformation that aligns the shapes as best as possible and decreases geometrical differences between them. The next step consists in searching the progressive transformations of one object toward the other one, that iteratively adds or suppresses pixels. These operations are based on geodesic distance transformation and lead to an optimal (linear) algorithm.