Neural network based adaptive image segmentation

Dinggang Shen, Qi Feihu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

It is difficult to separate objects from background by means of thresholding, in conditions of poor and nonuniform illumination. In this paper, we present a neuralcomputing approach for image segmentation via adaptive thresholding. The thresholding surface is calculated by interpolating the image gray levels at points where the Laplacian is high, indicating probable object edges. The interpolation in the image plane is completed by Hopfield neural network. In the experiments, we show that our method is better than the global thresholding method.

Original languageEnglish
Title of host publicationNational Conference Publication - Institution of Engineers, Australia
Editors Anon
PublisherIE Aust
Pages1035-1038
Number of pages4
Volume2
Edition94 /9
Publication statusPublished - 1994
Externally publishedYes
EventProceedings of the International Symposium on Information Theory & Its Applications 1994. Part 1 (of 2) - Sydney, Aust
Duration: 1994 Nov 201994 Nov 24

Other

OtherProceedings of the International Symposium on Information Theory & Its Applications 1994. Part 1 (of 2)
CitySydney, Aust
Period94/11/2094/11/24

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Shen, D., & Feihu, Q. (1994). Neural network based adaptive image segmentation. In Anon (Ed.), National Conference Publication - Institution of Engineers, Australia (94 /9 ed., Vol. 2, pp. 1035-1038). IE Aust.