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
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