Skeletonizing by compressed line adjacency graph in two directions

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.