Recommended Citation
Postprint version. Published in 2011 IEEE International Conference on Information and Automation Proceedings: Shenzhen, China, June 6, 2011, pages 343-348.
The definitive version is available at https://doi.org/10.1109/ICINFA.2011.5949014.
Abstract
Edge detection is an important but rather difficult task in image processing and analysis. In this research, artificial neural networks are employed for edge detection based on its adaptive learning and nonlinear mapping properties. Fuzzy sets are introduced during the training phase to improve the generalization ability of neural networks. The application of the proposed neural network approach to the edge detection of medical images for automated bladder cancer diagnosis is also investigated. Successful computer simulation results are obtained.
Disciplines
Electrical and Computer Engineering
Copyright
2011 IEEE.
Publisher statement
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URL: https://digitalcommons.calpoly.edu/eeng_fac/242