DocumentCode :
162311
Title :
Texture analysis for deep seabed type classification based on multifractal spectrum
Author :
Yan Li ; Yan Huang ; Puqiang Zhu ; Yeteng Luo ; Kai Sun
Author_Institution :
State Key Lab. of Robot., Shenyang Inst. of Autom., Shenyang, China
fYear :
2014
fDate :
7-10 April 2014
Firstpage :
1
Lastpage :
4
Abstract :
In order to perform autonomous manipulation in underwater surveys, a robust seabed type classification technique is crucial. Seabed images convey a lot of information about seabed types and various image segmentation methods have been implemented to classify seabed types by analyzing the features of images such as contour and region. However, these strategies are not robust for diverse underwater environments. Therefore, this paper proposes a novel method based on multifractal spectrum to descript and classify the deep seabed types by analyzing the textures. The applicability of multifractal approach to seabed type classification is verified by different sample images of deep seabed.
Keywords :
geophysical image processing; image classification; image texture; oceanographic techniques; classify seabed types; deep seabed type classification; deep seabed types; diverse underwater environments; image segmentation methods; multifractal approach; multifractal spectrum; sample images; texture analysis; Acoustics; Feature extraction; Fractals; Robots; Robustness; Sonar; Underwater vehicles; multifractal spectrum; seabed type classification; texture analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
OCEANS 2014 - TAIPEI
Conference_Location :
Taipei
Print_ISBN :
978-1-4799-3645-8
Type :
conf
DOI :
10.1109/OCEANS-TAIPEI.2014.6964533
Filename :
6964533
Link To Document :
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