Semantic graph and arc consistency in “true” three dimensional image labelling

Author

Deruyver, A. ; Hodé, Y.

Author_Institution

Dept. d´´Inf, IUT Strasbourg Sud, Illkirch, France

Volume

2

fYear

1995

fDate

23-26 Oct 1995

Firstpage

619

Abstract

This paper presents a new algorithm for arc consistency working on dataset containing over-segmented objects without previous knowledge about this over-segmentation. We introduce in the algorithm of Mohr and Henderson [1986] the notion of transitivity between regions which seem belonging to the same object. This algorithm has been tested on “true” three dimensional images. The tests made on a set of 20 nuclear resonance magnetic cerebral images show the reliability of this method to identify the three dimensional objects of the brain

Keywords

biomedical NMR; brain; graph theory; image recognition; image segmentation; medical image processing; object recognition; algorithm; arc consistency; brain; nuclear resonance magnetic cerebral images; object; over-segmented objects; semantic graph consistency; transitivity; true three dimensional image labelling; Brain; Image analysis; Image segmentation; Information analysis; Knowledge representation; Labeling; Magnetic resonance imaging; Nuclear magnetic resonance; Pattern recognition; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1995. Proceedings., International Conference on

Conference_Location

Washington, DC

Print_ISBN

0-8186-7310-9

Type

conf

DOI

10.1109/ICIP.1995.537555

Filename

537555