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 :
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