Study on blurry and smudgy path recognition by fuzzy neural network

Author

Wang, Rongben ; Ji, Shouwen ; Wang, Zhizhong ; Guo, Keyou

Author_Institution

Transp. of Coll., Jilin Univ., Changchun, China

Volume

1

fYear

2002

fDate

17-21 June 2002

Firstpage

160

Abstract

The methods of recognizing blurry and smudgy navigation path are studied by using fuzzy neural network for JLUIV-2 vision navigation intelligent vehicle. Two fuzzy neural network models are developed, one model has 5 layers, and uses normal distribution probability function as its fuzzy function, another model has 6 layers, and uses π function as its fuzzy function. The dynamic BP algorithm is used to train the two fuzzy neural networks. Experiments of the path recognizing and practical autonomous navigation are done by using JLUIV-2 intelligent vehicle. The results show that the two fuzzy neural networks can effectively recognize the blurry and smudgy navigation path.

Keywords

backpropagation; computer vision; driver information systems; fuzzy neural nets; image recognition; probability; road vehicles; JLUIV-2 vision navigation intelligent vehicle; backpropagation; blurry path recognition; dynamic BP algorithm; fuzzy neural network; fuzzy neural network models; normal distribution probability function; smudgy path recognition; Artificial neural networks; Automatic control; Charge coupled devices; Fuzzy neural networks; Gaussian distribution; Image recognition; Intelligent vehicles; Navigation; Neural networks; Pixel;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Vehicle Symposium, 2002. IEEE

Print_ISBN

0-7803-7346-4

Type

conf

DOI

10.1109/IVS.2002.1187945

Filename

1187945