DocumentCode :
2119575
Title :
Ground nephogram classification based on textural feature extraction and neural networks
Author :
Zhang, Yonghong ; Lu, Xiaofeng ; Yuan, Yong ; Yu, Wenkai
Author_Institution :
College of Information and Control Engineering, Nanjing University of Information Science and Technology, 210044, China
fYear :
2010
fDate :
4-6 Dec. 2010
Firstpage :
3737
Lastpage :
3740
Abstract :
The problem of ground nephogram classification using textural feature extraction and neural networks is considered in this paper. For cloud recognition, we use feature extraction based on co-occurrence matrices, and neural network classifiers for identifying cloud types in test images. This exhaustive testing gives us a better understanding of the strengths and limitations of different feature extraction methods and classification techniques on the given problem.
Keywords :
Artificial neural networks; Clouds; Copper; Correlation; Feature extraction; Image classification; Training; BPNN; Ground nephoram; Textural feature; classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Engineering (ICISE), 2010 2nd International Conference on
Conference_Location :
Hangzhou, China
Print_ISBN :
978-1-4244-7616-9
Type :
conf
DOI :
10.1109/ICISE.2010.5690096
Filename :
5690096
Link To Document :
بازگشت