STRUCTURAL DESCRIPTION OF LINE IMAGES BY THE CROSS SECTION SEQUENCE GRAPH
Toshihiro Suzuki, Shunji Mori · International Journal of Pattern Recognition and Artificial Intelligence · 1993
In this paper, we propose the Cross Section Sequence Graph which describes line images in a simple and well structured form. It is composed of regular regions called cross section sequences and singular regions. A cross section sequence is a sequence of cross sections, each of which is constructed as a pair of boundary points almost perpendicular to the direction of the line. The sequence corresponds to a straight or curved line segment. The remaining regions are extracted as singular regions, each of which corresponds to an end point region, corner, branch, cross, and so on. The cross section sequence graph is useful for many kinds of feature extraction, especially for skeletonization since a singular region can be analyzed from adjacent regular regions. Experimental results show that the skeleton extracted from the cross section sequence graph is better than that of a pixel-wise skeletonization (thinning) in terms of both processing speed and the quality of the skeleton.