Line Thinning via Merge-Split in Run-Length Sequences of Line Cross Sections
Gongzhu Hu, Ze-Nian Li · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1990
Thinning is an image processing procedure that extracts the medial axes, or skeletons, of objects in a binary image. Because of the iterative pixel-removing strategy used, most existing thinning algorithms are either inefficient (sequential algorithms) or need special hardware (parallel algorithms). Furthermore, for line-shaped objects, the line intersections produced by these algorithms tend to be elongated. A new line thinning and intersection detection approach is presented in this paper that deals with images in which objects are lines (curves). It uses run-length representation for the lines in the image. A histogram of run length is consulted to identify runs that correspond to line cross sections. The mid-points of the selected runs are used to form the skeletons. Line intersections are detected at locations where the sequences of runs merge or split. This approach is non-iterative with a time complexity linear to the size of the image.