Line Thinning via Merge-Split in Run-Length Sequences of Line Cross Sections

Gongzhu Hu; Ze-Nian Li

doi:10.1117/12.969732

1 March 1990 Line Thinning via Merge-Split in Run-Length Sequences of Line Cross Sections

Gongzhu Hu, Ze-Nian Li

Proceedings Volume 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques; (1990) https://doi.org/10.1117/12.969732
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States

Abstract

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.

Citation Download Citation

Gongzhu Hu and Ze-Nian Li "Line Thinning via Merge-Split in Run-Length Sequences of Line Cross Sections", Proc. SPIE 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques, (1 March 1990); https://doi.org/10.1117/12.969732

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