Departmental Papers (CIS)

Document Type

Journal Article

Date of this Version

March 2008

Comments

Postprint version. Published in Journal of Mathematical Imaging and Vision, Volume 30, Issue 3, March 2008, pages 249-274.
Publisher URL: http://dx.doi.org/10.1007/s10851-007-0054-1

Abstract

We present here a new randomized algorithm for repairing the topology of objects represented by 3D binary digital images. By "repairing the topology", we mean a systematic way of modifying a given binary image in order to produce a similar binary image which is guaranteed to be well-composed. A 3D binary digital image is said to be well-composed if, and only if, the square faces shared by background and foreground voxels form a 2D manifold. Well-composed images enjoy some special properties which can make such images very desirable in practical applications. For instance, well-known algorithms for extracting surfaces from and thinning binary images can be simplified and optimized for speed if the input image is assumed to be well-composed. Furthermore, some algorithms for computing surface curvature and extracting adaptive triangulated surfaces, directly from the binary data, can only be applied to well-composed images. Finally, we introduce an extension of the aforementioned algorithm to repairing 3D digital multivalued images. Such an algorithm finds application in repairing segmented images resulting from multi-object segmentations of other 3D digital multivalued images.

Keywords

well-composed images, digital topology, randomized algorithms

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Date Posted: 18 March 2008

This document has been peer reviewed.