Thin nets and crest lines: application to satellite data andmedical images
Monga, O.
Armande, N.
Montesinos, P.
Inst. Nat. de Recherche en Inf. et Autom., Le Chesnay;
This paper appears in: Image Processing, 1995. Proceedings., International Conference on
Publication Date: 23-26 Oct 1995
Volume: 2,
On page(s): 468-471 vol.2
Meeting Date: 10/23/1995 - 10/26/1995
Location: Washington, DC, USA
ISBN: 0-8186-3122-2
References Cited: 23
INSPEC Accession Number: 5241992
Digital Object Identifier: 10.1109/ICIP.1995.537517
Current Version Published: 2002-08-06
Abstract
We describe a new approach for extracting crest lines and thin
nets. The key point of our approach 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. Using an adapted scale factor, we apply this
approach to the extraction of roads in satellite data and blood vessels
in medical images. We also apply this method to the extraction of the
crest lines in depth maps of human faces
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