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Proceedings Paper

Segmentation using neural networks for automatic thresholding
Author(s): Alan V. Scherf; Gregory Allen Roberts
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Paper Abstract

A neural network solution to the problem of automatic threshold selection for image segmentation is presented. A multilayer perceptron is trained on a set of feature vectors extracted from gray scale imagery. The trained network then emulates the threshold selection behavior of its teacher. The thresholds obtained are used by a region based segmentation algorithm to partition the meaningful objects in the image into regions of constant gray level. Experimental results are given for a set of infrared imagery. 1.

Paper Details

Date Published: 1 August 1990
PDF: 7 pages
Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); doi: 10.1117/12.21162
Show Author Affiliations
Alan V. Scherf, Ford Aerospace Corp. (United States)
Gregory Allen Roberts, Ford Aerospace Corp. (United States)


Published in SPIE Proceedings Vol. 1294:
Applications of Artificial Neural Networks
Steven K. Rogers, Editor(s)

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