An Improved Fuzzy Neuron Network Scheme Using the Modified Genetic Algorithm and Structure

Author

Zhou, Lixiang ; Shen, Minfen ; Cai, Binghuang

Author_Institution

Coll. of Eng., Shantou Univ., Guangdong

Volume

4

fYear

2006

fDate

16-20 2006

Abstract

In the process of image filtering, it is a difficult problem to get rid of the distorted points and to keep the detail of the image at same time. So we use the fuzzy neuron network (FNN) to fuse the result of filter of the multilevel FIR-median hybrid (MFMHF) and the result of the median filter with a 5*5 window. It is not easy to set the appropriate parameters for the FNN. Thus, an improved FNN based on genetic algorithm (GA) is introduced to solve the problems of setting parameters of the FNN. Simulation results indicate that after the parameters of the FNN being optimized with GA, the performance of the FNN on image fusion is better than the performance of the common FNN

Keywords

FIR filters; fuzzy neural nets; genetic algorithms; image fusion; median filters; fuzzy neuron network scheme; genetic algorithm; image filtering; image fusion; modified genetic algorithm; multilevel FIR-median hybrid filter; Backpropagation; Educational institutions; Filters; Fuses; Fuzzy neural networks; Genetic algorithms; Genetic engineering; Image fusion; Neurons; Nonlinear systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, 2006 8th International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-9736-3

Electronic_ISBN

0-7803-9736-3

Type

conf

DOI

10.1109/ICOSP.2006.346135

Filename

4129827