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On curvature estimation of ISO surfaces in 3D gray-value images and the computation of shape descriptors

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Rieger,  B.
Department of Molecular Biology, MPI for biophysical chemistry, Max Planck Society;

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Citation

Rieger, B., Timmermans, F. J., van Vliet, L. J., & Verbeek, P. W. (2004). On curvature estimation of ISO surfaces in 3D gray-value images and the computation of shape descriptors. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(8), 1088-1094. Retrieved from http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=1307015&isnumber=29017.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0012-ED15-D
Abstract
In this paper, we present a novel method to estimate curvature of iso gray-level surfaces in gray-value images. Our method succeeds where standard isophote curvature estimation methods fail. There is neither a segmentation of the surface needed nor a parametric model assumed. Our estimator works on the orientation field of the surface. This orientation field and a description of local structure is obtained by the Gradient Structure Tensor. The estimated orientation field has iscontinuities mod π . It is mapped via the Knutsson mapping to a continuous representation. The principal curvatures of the surface, a coordinate invariant property, are computed in this mapped representation. From these curvatures, locally the bending energy is computed to describe the surface shape. An extensive evaluation shows that our curvature estimation is robust even in the presence of noise, independent of the scale of the object and furthermore the relative error stays small.