2-dimensional color sensor with combined neural network

Author

Takahashi, Masaharu ; Ando, Hideki

Author_Institution

Yamatake-Honeywell Co. Ltd., Kanagawa

fYear

1991

fDate

8-14 Jul 1991

Abstract

Summary form only given. A 2D color sensor has been developed to identify objects using color image data. When using this sensor the user must set several parameters for each object and this setting procedure is difficult using conventional methods. An approach to automatic parameter setting for identification by using a combined neural network has been developed. This combined neural network is composed of two network models. The method extracts the object´s feature distribution in red-green space using the Kohonen feature map. Feature vectors are made from these distributions. The feature vectors are used to train a multilayer network by the back-propagation method for identification

Keywords

colour; computer vision; computerised pattern recognition; image sensors; neural nets; self-organising storage; 2D color sensor; Kohonen feature map; automatic parameter setting; back-propagation; color image data; combined neural network; feature distribution; identification; multilayer network; red-green space; Color; Feature extraction; Image sensors; Multi-layer neural network; Neural networks; Production facilities;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on

Conference_Location

Seattle, WA

Print_ISBN

0-7803-0164-1

Type

conf

DOI

10.1109/IJCNN.1991.155521

Filename

155521