Properties of Gauss Digitized Shapes and Digital Surface Integration

This paper presents new topological and geometric properties of Gauss digitizations of Euclidean shapes, most of them holding in arbitrary dimension d. We focus on r-regular shapes sampled by Gauss digitization at gridstep h. The digitized boundary is shown to be close to the Euclidean boundary in the Hausdorff sense, the minimum distance $$\frac{\sqrt{d}}{2}h$$d2h being achieved by the projection map $$\xi $$ξ induced by the Euclidean distance. Although it is known that Gauss digitized boundaries may not be manifold when $$d \ge 3$$d≥3, we show that non-manifoldness may only occur in places where the normal vector is almost aligned with some digitization axis, and the limit angle decreases with h. We then have a closer look at the projection of the digitized boundary onto the continuous boundary by $$\xi $$ξ. We show that the size of its non-injective part tends to zero with h. This leads us to study the classical digital surface integration scheme, which allocates a measure to each surface element that is proportional to the cosine of the angle between an estimated normal vector and the trivial surface element normal vector. We show that digital integration is convergent whenever the normal estimator is multigrid convergent, and we explicit the convergence speed. Since convergent estimators are now available in the literature, digital integration provides a convergent measure for digitized objects.

[1]  R.M. McElhaney,et al.  Algorithms for graphics and image processing , 1983, Proceedings of the IEEE.

[2]  Marinette Revenu,et al.  Fast computation of the normal vector field of the surface of a 3-D discrete object , 1996, DGCI.

[3]  André Lieutier,et al.  Reconstructing shapes with guarantees by unions of convex sets , 2010, SCG.

[4]  Valentin E. Brimkov,et al.  Digital Geometry Algorithms , 2012 .

[5]  François de Vieilleville,et al.  Fast, accurate and convergent tangent estimation on digital contours , 2007, Image Vis. Comput..

[6]  T. O’Neil Geometric Measure Theory , 2002 .

[7]  Joakim Lindblad,et al.  Surface area estimation of digitized 3D objects using weighted local configurations , 2005, Image Vis. Comput..

[8]  Jean-Marie Morvan,et al.  Generalized Curvatures , 2008, Geometry and Computing.

[9]  J. Stoer,et al.  On piecewise linear approximation of planar Jordan curves , 1994 .

[10]  Jean Serra,et al.  Image Analysis and Mathematical Morphology , 1983 .

[11]  Azriel Rosenfeld,et al.  Digital geometry - geometric methods for digital picture analysis , 2004 .

[12]  A. Gorin ON THE VOLUME OF TUBES , 1983 .

[13]  Longin Jan Latecki 3D Well-Composed Pictures , 1997, CVGIP Graph. Model. Image Process..

[14]  Longin Jan Latecki,et al.  Digitizations preserving shape , 1999, Pattern Recognit..

[15]  Frédéric Chazal,et al.  Smooth manifold reconstruction from noisy and non-uniform approximation with guarantees , 2008, Comput. Geom..

[16]  Leonidas J. Guibas,et al.  Voronoi-Based Curvature and Feature Estimation from Point Clouds , 2011, IEEE Transactions on Visualization and Computer Graphics.

[17]  Jacques-Olivier Lachaud,et al.  Voronoi-Based Geometry Estimator for 3D Digital Surfaces , 2014, DGCI.

[18]  Jacques-Olivier Lachaud,et al.  Multigrid convergent principal curvature estimators in digital geometry , 2014, Comput. Vis. Image Underst..

[19]  M. Huxley Exponential sums and lattice points III , 2003 .

[20]  Frédéric Chazal,et al.  Normal cone approximation and offset shape isotopy , 2009, Comput. Geom..

[21]  François de Vieilleville,et al.  Convex Digital Polygons, Maximal Digital Straight Segments and Convergence of Discrete Geometric Estimators , 2007, Journal of Mathematical Imaging and Vision.

[22]  Peer Stelldinger,et al.  A topological sampling theorem for Robust boundary reconstruction and image segmentation , 2009, Discret. Appl. Math..

[23]  Mohamed Tajine,et al.  Topological properties of Hausdorff discretization, and comparison to other discretization schemes , 2002, Theor. Comput. Sci..

[24]  Longin Jan Latecki,et al.  Digitizations Preserving Topological and Differential Geometric Properties , 1995, Comput. Vis. Image Underst..

[25]  Jean-Claude Paul,et al.  Surface area estimation of digitized 3D objects using quasi-Monte Carlo methods , 2010, Pattern Recognit..

[26]  Reinhard Klette,et al.  Digital Planar Segment Based Polyhedrization for Surface Area Estimation , 2001, IWVF.

[27]  Peer Stelldinger,et al.  Topological Equivalence between a 3D Object and the Reconstruction of Its Digital Image , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[28]  James C. Gee,et al.  Topological Repairing of 3D Digital Images , 2008, Journal of Mathematical Imaging and Vision.

[29]  Frédéric Chazal,et al.  Stability of Curvature Measures , 2008, Comput. Graph. Forum.

[30]  Johanna Fasciati-Ziegel,et al.  Estimation of surface area and surface area measure of three-dimensional sets from digitizations , 2010, Image Vis. Comput..

[31]  Rémy Malgouyres,et al.  Convergence of Binomial-Based Derivative Estimation for C2 Noisy Discretized Curves , 2009, DGCI.

[32]  Yan Gérard,et al.  Estimation of the Derivatives of a Digital Function with a Convergent Bounded Error , 2011, DGCI.

[33]  Reinhard Klette,et al.  Surface area estimation for digitized regular solids , 2000, SPIE Optics + Photonics.

[34]  Stephen Smale,et al.  Finding the Homology of Submanifolds with High Confidence from Random Samples , 2008, Discret. Comput. Geom..

[35]  Christopher Conrad,et al.  Preserving Topology by a Digitization Process , 1998, Journal of Mathematical Imaging and Vision.

[36]  Theo Pavlidis,et al.  Algorithms for Graphics and Imag , 1983 .

[37]  Tristan Roussillon,et al.  Multigrid Convergence of Discrete Geometric Estimators , 2012 .

[38]  Jacques-Olivier Lachaud,et al.  Integral Based Curvature Estimators in Digital Geometry , 2013, DGCI.

[39]  Frédéric Chazal,et al.  Boundary Measures for Geometric Inference , 2010, Found. Comput. Math..

[40]  Mohamed Tajine,et al.  Discretization in Hausdorff Space , 2004, Journal of Mathematical Imaging and Vision.

[41]  Jacques-Olivier Lachaud,et al.  Espaces non-euclidiens et analyse d'image : modèles déformables riemanniens et discrets, topologie et géométrie discrète. (Non-Euclidean spaces and image analysis : Riemannian and discrete deformable models, discrete topology and geometry) , 2006 .

[42]  Reinhard Klette,et al.  Multigrid Convergence of Calculated Features in Image Analysis , 2000, Journal of Mathematical Imaging and Vision.

[43]  Peer Stelldinger,et al.  Towards a general sampling theory for shape preservation , 2005, Image Vis. Comput..

[44]  François de Vieilleville,et al.  Maximal digital straight segments and convergence of discrete geometric estimators , 2005, SCIA.

[45]  Laure Tougne,et al.  Multigrid Convergence and Surface Area Estimation , 2002, Theoretical Foundations of Computer Vision.