DocumentCode :
2595858
Title :
Skeletonizing by compressed line adjacency graph in two directions
Author :
Xingyuan, Li ; Weon-Geun, Oh ; Jiarong, Hong
Author_Institution :
AI Div., Syst. Eng. Res. Inst., Taejon, South Korea
Volume :
3
fYear :
1996
fDate :
16-19 Sep 1996
Firstpage :
17
Abstract :
Now all the block based skeletonizing algorithms only use the compressed line adjacency graph scanned in one direction. For lines approximately parallel to the scan direction, there is difficulty extracting the skeleton because such a line may be separated into several graph nodes or mixed with some pixels of other lines in the intersection point. In this paper, we propose a new skeletonizing method by combining c-LAG of horizontal and vertical direction. The main idea of the method is a rule for the skeletons in horizontal and vertical direction c-LAG and knowledge based node validation. The validation makes full use of global information in the image. It has been tested on a large amount of characters and high quality achieved
Keywords :
data compression; edge detection; feature extraction; graph theory; mathematical morphology; block based skeletonizing algorithms; compressed line adjacency graph; global information; graph nodes; image processing; intersection point; knowledge based node validation; scan direction; two directions; Artificial intelligence; Computer science; Image coding; Image segmentation; Partitioning algorithms; Pixel; Skeleton; Systems engineering and theory; Testing; Topology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 1996. Proceedings., International Conference on
Conference_Location :
Lausanne
Print_ISBN :
0-7803-3259-8
Type :
conf
DOI :
10.1109/ICIP.1996.560358
Filename :
560358
Link To Document :
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