Segmentation using neural networks for automatic thresholding

Alan V. Scherf; Gregory Allen Roberts

doi:10.1117/12.21162

1 August 1990 Segmentation using neural networks for automatic thresholding

Alan V. Scherf, Gregory Allen Roberts

Proceedings Volume 1294, Applications of Artificial Neural Networks; (1990) https://doi.org/10.1117/12.21162
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

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.

Citation Download Citation

Alan V. Scherf and Gregory Allen Roberts "Segmentation using neural networks for automatic thresholding", Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); https://doi.org/10.1117/12.21162

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