A complex texture classification algorithm based on Gabor-type filtering cellular neural networks and self-organized fuzzy inference neural networks

Author

Lin, Chin-Teng ; Huang, Chao-Hui

Author_Institution

Dept. Electr. & Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan

fYear

2005

fDate

23-26 May 2005

Firstpage

3942

Abstract

In this paper, a bio-inspired complex texture classification algorithm has been introduced. This algorithm included two neural networks; one is the Gabor-type filtering cellular neural network which is used to simulate the human retina, the other is the self-organized fuzzy inference neural network which is used to simulate the brain. Both the neural networks can be considered as feedforward neural networks. Thus, we can say that the whole system which has been introduced in this paper is also a feedforward system and it contains the ability for parallel processing.

Keywords

brain models; cellular neural nets; eye; feedforward neural nets; fuzzy neural nets; image classification; image texture; inference mechanisms; parallel architectures; self-organising feature maps; Gabor-type filtering; bio-inspired complex texture classification; brain; cellular neural networks; complex texture classification algorithm; feedforward neural networks; human retina; parallel processing; self-organized fuzzy inference neural networks; Biological neural networks; Brain modeling; Cellular neural networks; Classification algorithms; Feedforward neural networks; Filtering algorithms; Fuzzy neural networks; Gabor filters; Inference algorithms; Neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2005. ISCAS 2005. IEEE International Symposium on

Print_ISBN

0-7803-8834-8

Type

conf

DOI

10.1109/ISCAS.2005.1465493

Filename

1465493