Perfect image segmentation using pulse coupled neural networks

Author

Kuntimad, G. ; Ranganath, H.S.

Author_Institution

Rocketdyne Div., Boeing North American, Huntsville, AL, USA

Volume

10

Issue

3

fYear

1999

fDate

5/1/1999 12:00:00 AM

Firstpage

591

Lastpage

598

Abstract

This paper describes a method for segmenting digital images using pulse coupled neural networks (PCNN). The pulse coupled neuron (PCN) model used in PCNN is a modification of the cortical neuron model of Eckhorn et al. (1990). A single layered laterally connected PCNN is capable of perfectly segmenting digital images even when there is a considerable overlap in the intensity ranges of adjacent regions. Conditions for perfect image segmentation are derived. It is also shown that addition of an inhibition receptive field to the neuron model increases the possibility of perfect segmentation. The inhibition input reduces the overlap of intensity ranges of adjacent regions by effectively compressing the intensity range of each region

Keywords

image segmentation; neural nets; adjacent regions; cortical neuron model; digital images; inhibition receptive field; intensity range overlap; perfect image segmentation; pulse coupled neural networks; single-layered laterally connected PCNN; Artificial neural networks; Bridges; Brightness; Digital images; Image processing; Image segmentation; Neural networks; Neurons; Personal communication networks; Pixel;

fLanguage

English

Journal_Title

Neural Networks, IEEE Transactions on

Publisher

ieee

ISSN

1045-9227

Type

jour

DOI

10.1109/72.761716

Filename

761716