Image segmentation using modified neural network techniques

V. E. Gold Jr.; Darrel L. Chenoweth; John E. Selvage

doi:10.1117/12.234265

4 March 1996 Image segmentation using modified neural network techniques

V. E. Gold Jr., Darrel L. Chenoweth, John E. Selvage

Proceedings Volume 2664, Applications of Artificial Neural Networks in Image Processing; (1996) https://doi.org/10.1117/12.234265
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States

Abstract

This paper describes an application of neural networks in segmenting gray shade images. It describes a method for ranking pixel features relative to their ability to discriminate among different image segment classes. A neural classifier is proposed which operates on pixel feature vectors as inputs to the network, each feature having a variable weight. The weights are iteratively changed to obtain dense and highly separated clusters. The resulting weights are indicative of the usefulness, or rank, of the features.

Citation Download Citation

V. E. Gold Jr., Darrel L. Chenoweth, and John E. Selvage "Image segmentation using modified neural network techniques", Proc. SPIE 2664, Applications of Artificial Neural Networks in Image Processing, (4 March 1996); https://doi.org/10.1117/12.234265

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