Shape Variability and Spatial Relationships Modeling in Statistical Pattern Recognition

Abstract : We focus on the problem of shape variability modeling in statistical pattern recognition. We present a nonlinear statistical model invariant to affine transformations. This model is learned on an ordinate set of points. The concept of relations between model components is also taken in account. This model is used to find curves and points partially occulted in the image. We present its application on medical imaging in cephalometry.
Type de document :
Article dans une revue
Pattern Recognition Letters, Elsevier, 2004, 25 (2), pp.239-247
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https://hal.archives-ouvertes.fr/hal-00263583
Contributeur : Marinette Revenu <>
Soumis le : lundi 4 février 2013 - 14:44:55
Dernière modification le : mardi 5 juin 2018 - 10:14:42

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  • HAL Id : hal-00263583, version 1

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Barbara Romaniuk, Michel Desvignes, Marinette Revenu, Marie-Josèphe Deshayes. Shape Variability and Spatial Relationships Modeling in Statistical Pattern Recognition. Pattern Recognition Letters, Elsevier, 2004, 25 (2), pp.239-247. 〈hal-00263583〉

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