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 language | English |
|---|---|
| Pages (from-to) | 1035-1038 |
| Number of pages | 4 |
| Journal | National Conference Publication - Institution of Engineers, Australia |
| Volume | 2 |
| Issue number | 94 /9 |
| Publication status | Published - 1994 |
| Event | Proceedings of the International Symposium on Information Theory & Its Applications 1994. Part 1 (of 2) - Sydney, Aust Duration: 1994 Nov 20 → 1994 Nov 24 |
ASJC Scopus subject areas
- General Engineering