DocumentCode :
654067
Title :
Adaptive Multi-Feature Fusion for underwater diver classification
Author :
Yang Juan ; Xu Feng ; Wei Zhiheng ; An Xudong ; Liu Jia ; Ji Yongqiang ; Wen Tao
Author_Institution :
Image Sonar Technol. Lab., Inst. of Acoust., Beijing, China
fYear :
2013
fDate :
24-26 July 2013
Firstpage :
1
Lastpage :
4
Abstract :
This paper discusses a technique for the classification of divers, underwater vehicles and other similar targets based on adaptive multi-feature fusion. This technique mainly uses target features, e.g., image feature, moment feature and HRRP (high resolution range profile) features selected by an Adaptive Feature Fusion method. The sea trial data collected in Sanya in January, 2009 are processed by the algorithm. Real data processing results demonstrate the Adaptive Multi-Feature Fusion based technique can effectively reduce the error probability.
Keywords :
error statistics; feature extraction; image classification; image fusion; HRRP feature; Sanya; adaptive feature fusion method; adaptive multifeature fusion; adaptive multifeature fusion-based technique; error probability reduction; high-resolution range profile feature; image feature; moment feature; real data processing; sea trial data; target features; underwater diver classification; underwater vehicles; Adaptation models; Classification algorithms; Feature extraction; Sonar detection; Sonar equipment; Underwater vehicles; adaptive feature selection; diver; high resolution range profile; multi-feature fusion; underwater target classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics in Underwater Geosciences Symposium (RIO Acoustics), 2013 IEEE/OES
Conference_Location :
Rio de Janeiro
Type :
conf
DOI :
10.1109/RIOAcoustics.2013.6684022
Filename :
6684022
Link To Document :
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