Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-23T04:59:20.102Z Has data issue: false hasContentIssue false

A LIMITATION OF THE ESTIMATION OF INTRINSIC VOLUMES VIA PIXEL CONFIGURATION COUNTS

Published online by Cambridge University Press:  28 March 2014

Jürgen Kampf*
Affiliation:
FB Mathematik, TU Kaiserslautern, Postbox 3049, 67653 Kaiserslautern,Germany email [email protected]
Get access

Abstract

It is often helpful to compute the intrinsic volumes of a set of which only a pixel image is observed. A computationally efficient approach, which is suggested by several authors and used in practice, is to approximate the intrinsic volumes by linear combinations of the pixel configuration counts. However, we will show that when this approach is used for the computation of an intrinsic volume other than volume or surface area, an asymptotic error of 100% of the correct value cannot be avoided. As a consequence we derive that estimators which ignore the data and return constant values are optimal with respect to a natural criterion which has already been applied successfully for the estimation of the surface area.

Type
Research Article
Copyright
Copyright © University College London 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Gray, S. B., Local properties of binary images in two dimensions. IEEE Trans. Comput. C-20 (1971), 551–561.CrossRefGoogle Scholar
Kiderlen, M., Estimating the Euler characteristic of a planar set from a digital image. J. Vis. Commun. Image R. 17 2006, 12371255.Google Scholar
Kiderlen, M. and Rataj, J., On infinitesimal increase of volumes of morphological transforms. Mathematika 53 2006, 103127.CrossRefGoogle Scholar
Kiderlen, M. and Ziegel, J., Estimation of surface area and surface area measure of three-dimensional sets from digitizations. Image Vision Comput. 28 2010, 6477.Google Scholar
Lindblad, J., Surface area estimation of digitized 3D objects using weighted local configurations. Image Vision Comput. 23 2005, 111122.CrossRefGoogle Scholar
Ohser, J., Nagel, W. and Schladitz, K., Miles formulae for Boolean models observed on lattices. Image Anal. Stereol. 28 2009, 7792.Google Scholar
Ohser, J., Sandau, K., Kampf, J., Vecchio, I. and Moghiseh, A., Improved estimation of fibre length from 3-dimensional images. Image Anal. Stereol. 32 2013, 4555.CrossRefGoogle Scholar
Schneider, R., Convex Bodies: The Brunn–Minkowski Theory, Cambridge University Press (Cambridge, 1993).CrossRefGoogle Scholar
Schneider, R. and Weil, W., Stochastic and Integral Geometry, Springer (Berlin, Heidelberg, 2008).CrossRefGoogle Scholar
Svane, A. M., Local digital estimators of intrinsic volumes for Boolean models and in the design based setting. J. Appl. Probab. (SGSA) (to appear).Google Scholar
Svane, A. M., Local digital algorithms for estimating the mean integrated curvature of r-regular sets. CSGB Report 08/2012, available at http://pure.au.dk/portal/en/publications/local-digital-algorithms-for-estimating-the-mean-integrated-curvature-of-rregular-sets%283fea2a6b-0733-40a5-8f8d-68260511e884%29.html.Google Scholar
Svane, A. M., On multigrid convergence of local algorithms for intrinsic volumes. J. Math. Imaging Vision (to appear).Google Scholar