Skeleton pruning by contour partitioning with discrete curve evolution.
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Abstract
In this paper, we introduce a new skeleton pruning method based on contour partitioning. Any contour partition can be used, but the partitions obtained by Discrete Curve Evolution (DCE) yield excellent results. The theoretical properties and the experiments presented demonstrate that obtained skeletons are in accord with human visual perception and stable, even in the presence of significant noise and shape variations, and have the same topology as the original skeletons. In particular, we have proven that the proposed approach never produces spurious branches, which are common when using the known skeleton pruning methods. Moreover, the proposed pruning method does not displace the skeleton points. Consequently, all skeleton points are centers of maximal disks. Again, many existing methods displace skeleton points in order to produces pruned skeletons.
Medical subject headings
- Algorithms
- Artificial Intelligence
- Image Enhancement
- Image Interpretation, Computer-Assisted
- Pattern Recognition, Automated
- Signal Processing, Computer-Assisted