Automatic Detection of Sand Ripple Features in Sidescan Sonar Imagery

Abstract

A novel fingerprint analysis technique for automatic determination of seabed ripple features has been investigated. A method is required for automatically extracting from sidescan sonar seabed imagery the orientation and wavelength of ripples and also defect density. Defects in the ripple field are terminations or bifurcations of ripple crests. A rippled background increases the difficulty of finding objects in seabed imagery and the density of defects may prove to be useful as an objective parameter for quantifying this difficulty.

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Document Details

Document Type
Technical Report
Publication Date
Jul 09, 2014
Accession Number
AD1017003

Entities

People

  • Adam Skarke
  • Anna Crawford

Organizations

  • Defence Research and Development Canada

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Acoustic Attenuation
  • Algorithms
  • Aspect Angle
  • Automated Target Recognition
  • Autonomous Vehicles
  • Data Sets
  • Detection
  • Fingerprints
  • Geometry
  • Grazing Angles
  • Orientation (Direction)
  • Seabed
  • Sonar Images
  • Standards
  • Surveys
  • Target Recognition
  • Unmanned Maritime Systems

Readers

  • Coastal Oceanography
  • Computer Vision.