Extraction of thin nets in grey-level images using computational differential geometry
Abstract
In this paper, we describe a new approach for extracting thin nets in 2−D grey-level images. The key point is to model thin nets as the crest lines of the image surface. Crest lines are the lines where one of the two principal curvatures is locally extremal. We define these lines using first, second and third derivatives of the image. We compute the image derivatives using recursive filters approximating the Gaussian filter and its derivatives. This paper presents an algorithm to extract thin nets from 2−D images and we apply this method to the extraction of roads in satellite images.
Copyright © 2016 Nassar H. Abdel-All, M.A. Soliman, R.A. Hussein, Wadah M. El-Nini. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Cite this article
N. H. Abdel-All, M. A. Soliman, R. A. Hussein, W. M. El-Nini, Extraction of thin nets in grey-level images using computational differential geometry, J. Math. Comput. Sci. 6 (2016), 1047–1057.
BibTeX
@article{Abdel-All2016,
author = {Abdel-All, Nassar H. and Soliman, M.A. and Hussein, R.A. and El-Nini, Wadah M.},
title = {Extraction of thin nets in grey-level images using computational differential geometry},
journal = {J. Math. Comput. Sci.},
volume = {6},
year = {2016},
pages = {1047--1057},
doi = {}
}