A SOM neural network that reveals continuous displacement fields

Author

Labonte, Gilles

Author_Institution

Dept. of Math. & Comput. Sci., R. Mil. Coll. of Canada, Kingston, Ont., Canada

Volume

2

fYear

1998

fDate

4-9 May 1998

Firstpage

880

Abstract

We present a neural network algorithm, derived from the Kohonen self-organized mapping algorithm, for the solution of the problem of matching points in two pictures representing slightly displaced and distorted images of the same objects. We describe it hereafter in the context of a particular application, namely the matching of the images of marker-particles suspended in a moving fluid, seen in two pictures of them taken a small time interval apart. We illustrate the quality of the solutions it produces with representative results obtained for some test problems; in all cases it is outstandingly efficient

Keywords

fluid mechanics; image matching; physics computing; self-organising feature maps; Kohonen self-organized mapping algorithm; SOM neural network; continuous displacement fields; displaced images; distorted images; marker-particles; moving fluid; Biomedical imaging; Computer science; Educational institutions; Mathematics; Military computing; Neural networks; Remote sensing; Stereo vision; Testing; Visualization;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on

Conference_Location

Anchorage, AK

ISSN

1098-7576

Print_ISBN

0-7803-4859-1

Type

conf

DOI

10.1109/IJCNN.1998.685884

Filename

685884