Spatial to temporal conversion of images using a pulse-coupled neural network

Author

Brown, Eric L. ; Wilamowski, Bogdan M.

Author_Institution

Wyoming Univ., Laramie, WY, USA

Volume

4

fYear

1999

fDate

1999

Firstpage

2310

Abstract

An electronic model of a pulse-coupled neural network is proposed. The model exhibits very interesting features such as segmentation, feature extraction, orientation independence and noise tolerance. Segmentation means that the output pattern depends strongly on the spatial location of the pixels in respect to one other. Feature extraction means that if the input image includes several patterns, then it is very likely the temporal output is a superposition of features in that image. The output temporal pattern is independent of the orientation of image or orientation of fragments of the image. With relatively low noise (less than 10%) the output pattern is virtually independent of the noise

Keywords

feature extraction; image segmentation; neural nets; noise; electronic model; noise tolerance; orientation independence; pulse-coupled neural network; spatial-temporal conversion; Biological neural networks; Capacitance; Feature extraction; Image converters; Image segmentation; Nerve fibers; Neural networks; Neurons; Optical noise; Optical pulses;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1999. IJCNN '99. International Joint Conference on

Conference_Location

Washington, DC

ISSN

1098-7576

Print_ISBN

0-7803-5529-6

Type

conf

DOI

10.1109/IJCNN.1999.833424

Filename

833424