DocumentCode
390701
Title
Using neural network in color classification
Author
Yingjian, Qi ; Siwei, Luo ; Jianyu, Li ; Huakun, Huang
Author_Institution
Dept. of Comput. Sci. & Technol., Northern Jiaotong Univ., Beijing, China
Volume
1
fYear
2002
fDate
28-31 Oct. 2002
Firstpage
708
Abstract
The artificial neural network (ANN) has widely been used in the field of pattern classification. The main task of image segmentation is to extract interesting objects placed at different locations in images, so it is a sort of pattern classification problem. It can be treated as a maximum likelihood estimation problem in a color image when represented in a color histogram. In order to improve the flexibility of the classification result in a changed environment we propose the method of training the color pattern in a neural network using the EM algorithm which is a general method for the maximum likelihood problem. An experiment proved that it is applicable and significant.
Keywords
image classification; image colour analysis; image segmentation; maximum likelihood estimation; neural nets; EM algorithm; artificial neural network; color classification; color histogram; color image; image segmentation; maximum likelihood estimation problem; object extraction; pattern classification; training; Artificial neural networks; Color; Data mining; Gaussian distribution; Image segmentation; Intelligent networks; Maximum likelihood estimation; Neural networks; Pattern classification; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
TENCON '02. Proceedings. 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering
Print_ISBN
0-7803-7490-8
Type
conf
DOI
10.1109/TENCON.2002.1181372
Filename
1181372
Link To Document