Shape Preserving Digitization of Ideal and
Blurred Binary Images
Ullrich Köthe and Peer Stelldinger
in: I. Nyström, G. Sanniti di Baja, S. Svensson (eds.): Discrete Geometry for Computer Imagery, Proc. of 11th DGCI Conference, Naples 2003, Lecture Notes in Computer Science 2886, pp. 82-91, Heidelberg: Springer, 2003 (note: this article is © Springer-Verlag)
Abstract
In order to make image analysis methods more reliable it
is important to analyse to what extend shape information is preserved
during image digitization. Most existing approaches to this problem consider
topology preservation and are restricted to ideal binary images. We
extend these results in two ways. First, we characterize the set of binary
images which can be correctly digitized by both regular and irregular
sampling grids, such that not only topology is preserved but also the
Hausdorff distance between the original image and the reconstruction is
bounded. Second, we prove an analogous theorem for gray scale images
that arise from blurring of binary images with a certain filter type. These
results are steps towards a theory of shape digitization applicable to real
optical systems.
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