DocumentCode :
2151368
Title :
Sonar Images Classification of Seabed Physiognomy Based on the Information Fusion Methods
Author :
Sun, Ning ; Shim, Taebo
Volume :
2
fYear :
2008
fDate :
27-30 May 2008
Firstpage :
813
Lastpage :
819
Abstract :
As the exploration of the seabed is extended ever further, automated recognition and classification of sonar images become increasingly important. However, most of the related methods ignore the directional information and scale invariance or only pay attention to one of them. To deal with this problem, we combine 2D Gabor filters and fuzzy fractal dimension based on the information fusion method in this paper. The 2D Gabor filters are designed with constrained parameters to reduce the complexity and to improve the calculation efficiency. Meanwhile, at each orientation, the optimal parameters of the Gabor filters will be selected with the help of bandwidth parameters based on the Fisher criterion. Hybrid-fusion method and multilayer perceptron classifier are applied in the information fusion method. The approach proposed in this paper can overcome some disadvantages of the traditional approaches of extracting texture features, and improve recognition rate effectively.
Keywords :
Acoustic arrays; Acoustic beams; Data mining; Feature extraction; Fractals; Gabor filters; Image classification; Marine animals; Sonar; Underwater acoustics; Gabor filters; classification; fuzzy fractal dimension; information fusion; side scan sonar image;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing, 2008. CISP '08. Congress on
Conference_Location :
Sanya, China
Print_ISBN :
978-0-7695-3119-9
Type :
conf
DOI :
10.1109/CISP.2008.141
Filename :
4566417
Link To Document :
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