Ridge surfaces represent important features for the analysis of 3-dimensional
(3D) datasets in diverse applications and are often derived from varying
underlying data including flow fields, geological fault data, and point data,
but they can also be present in the original scalar images acquired using a
plethora of imaging techniques. Our work is motivated by the analysis of image
data acquired using micro-computed tomography (Micro-CT) of ancient, rolled and
folded thin-layer structures such as papyrus, parchment, and paper as well as
silver and lead sheets. From these documents we know that they are
2-dimensional (2D) in nature. Hence, we are particularly interested in
reconstructing 2D manifolds that approximate the document's structure. The
image data from which we want to reconstruct the 2D manifolds are often very
noisy and represent folded, densely-layered structures with many artifacts,
such as ruptures or layer splitting and merging. Previous ridge-surface
extraction methods fail to extract the desired 2D manifold for such challenging
data. We have therefore developed a novel method to extract 2D manifolds. The
proposed method uses a local fast marching scheme in combination with a
separation of the region covered by fast marching into two sub-regions. The 2D
manifold of interest is then extracted as the surface separating the two
sub-regions. The local scheme can be applied for both automatic propagation as
well as interactive analysis. We demonstrate the applicability and robustness
of our method on both artificial data as well as real-world data including
folded silver and papyrus sheets.Comment: 16 pages, 21 figures, to be published in IEEE Transactions on
Visualization and Computer Graphic