DocumentCode :
996762
Title :
Skeleton Pruning by Contour Partitioning with Discrete Curve Evolution
Author :
Bai, Xiang ; Latecki, Longin Jan ; Liu, Wen-yu
Author_Institution :
Dept. of Electron. & Inf., Huazhong Univ. of Sci. & Technol., Wuhan
Volume :
29
Issue :
3
fYear :
2007
fDate :
3/1/2007 12:00:00 AM
Firstpage :
449
Lastpage :
462
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
Keywords :
image representation; image thinning; object recognition; contour partitioning; discrete curve evolution; human visual perception; object recognition; object representation; skeleton pruning; Computer Society; Helium; Humans; Image retrieval; Noise generators; Noise shaping; Shape measurement; Skeleton; Topology; Visual perception; Skeleton; contour partition; discrete curve evolution.; skeleton pruning; Algorithms; Artificial Intelligence; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.2007.59
Filename :
4069261
Link To Document :
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