| Autor: |
S. Khunkay, K. Paithoonwattanakij |
| Rok vydání: |
2002 |
| Předmět: |
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| Zdroj: |
Proceedings of ICICS, 1997 International Conference on Information, Communications and Signal Processing. Theme: Trends in Information Systems Engineering and Wireless Multimedia Communications (Cat. No.97TH8237). |
| DOI: |
10.1109/icics.1997.652070 |
| Popis: |
We present a new algorithm that can segment fuzzy data. This method is based on fuzzy logic and neural network, and the concept of the constraint satisfaction problem (CSP). Firstly, pre-processing by creating a new pixel value based on the fuzzy rule has the ability to describe the effect of the neighborhood pixel on the degree of membership value or linguistic variables which are utilized to activate a rule base. Secondly, the feature extraction employs Kohonen (1982) feature mapping (SOM), which can learn a feature without prior knowledge. Finally, a fuzzy C-mean (FCM) adapts to the CSP structure by constituting a interconnection weight for all membership values of the fuzzy c-mean with a global consistency situation. The result of this method have been tested on a variety of images. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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