Seafloor characterization using texture

Author

Subramaniam, Suresh ; Barad, Herb ; Martinez, Andrew B. ; Bourgeois, Brian

Author_Institution

Dept. of Electr. Eng., Tulane Univ., New Orleans, LA, USA

fYear

1993

fDate

4-7 Apr 1993

Firstpage

0.833333333333333

Abstract

Texture analysis is performed on multibeam sonar imagery. A set of 14 texture features is computed using cooccurrence matrices to form the feature space. The dimensionality of the feature space is reduced by extracting the principal components from the original feature space. Classification of the image is performed on the principal components using the K-means algorithm. Results indicate that seafloor bottom types can be characterized by analyzing the texture of bathymetric sonar images

Keywords

bathymetry; feature extraction; geophysical signal processing; image classification; image texture; oceanographic techniques; seafloor phenomena; sonar imaging; underwater sound; K-means algorithm; bathymetric sonar images; clustering algorithm; cooccurrence matrices; feature space; image classification; multibeam sonar imagery; principal components extraction; seafloor bottom types; seafloor characterization; texture analysis; texture features; Data mining; Image analysis; Image texture analysis; Information analysis; Laboratories; Performance analysis; Sea floor; Sea floor roughness; Signal resolution; Sonar;

fLanguage

English

Publisher

ieee

Conference_Titel

Southeastcon '93, Proceedings., IEEE

Conference_Location

Charlotte, NC

Print_ISBN

0-7803-1257-0

Type

conf

DOI

10.1109/SECON.1993.465712

Filename

465712