Çelik, Turgay and Tjahjadi, Tardi (2011) A novel method for sidescan sonar image segmentation. IEEE Journal of Oceanic Engineering, Vol.36 (No.22). pp. 186-194. doi:10.1109/JOE.2011.2107250

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Abstract

In this paper, we propose a novel unsupervised algorithm for segmenting sidescan sonar images of seafloor. The proposed algorithm does not make any a priori assumption on the nature of the input sidescan sonar image. The algorithm first constructs a multiresolution representation of the input image using the forward and inverse undecimated discrete wavelet transform (UDWT). A feature vector is then extracted for each pixel using both intra-resolution and inter-resolution data. The dimensionality of each feature vector is reduced using principal component analysis (PCA). The feature vectors are then clustered into disjoint clusters using k-means clustering. The number of clusters is estimated automatically. Experimental results on real sonar images confirm the effectiveness of the proposed algorithm.

Item Type:	Journal Article
Subjects:	Q Science > QE Geology T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Science > Engineering
Library of Congress Subject Headings (LCSH):	Sidescan sonar, Principal components analysis, Ocean bottom, Image processing
Journal or Publication Title:	IEEE Journal of Oceanic Engineering
Publisher:	IEEE Oceanic Engineering Society
ISSN:	0364-9059
Official Date:	April 2011
Dates:	Date Event April 2011 Published
Volume:	Vol.36
Number:	No.22
Number of Pages:	9
Page Range:	pp. 186-194
DOI:	10.1109/JOE.2011.2107250
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Funder:	University of Warwick Vice Chancellor Scholarship

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