Robust Estimation of Adaptive Tensors of Curvature by Tensor Voting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of curvature based shape properties of surfaces in 3D grey-value images
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Predictive modeling of cardiac fiber orientation using the knutsson mapping
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part II
| Hi-index | 0.00 |
In this paper we present a novel method to estimate curvature of iso grey-level surfaces in grey-value images. Our method succeeds where isophote curvature fails. There is neither a segmentation of the surface needed nor a parametric model assumed. Our estimator works on the orientation (normal vector) 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 discontinuities mod 隆. It is mapped via the Knutsson mapping to a continuous representation. The principal curvatures of the surface, a coordinate invariant property, arecomputed in this mapped representation. An 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.