Departmental Papers (CIS)
Document Type
Journal Article
Date of this Version
March 2008
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
Date Posted: 18 March 2008
This document has been peer reviewed.
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