Automic Change Detection and Classification (ACDC) System

Abstract

The authors are developing an Automated Change Detection and Classification (ACDC) system for the Mine Warfare (MIW) group at the Naval Oceanographic Office (NAVOCEANO). ACDC detects features in sidescan imagery, classifies the features (e.g., as minelike or not), and searches through historical databases of previously detected features to perform change detection (i.e., to determine whether the feature is new or pre-existing, relative to earlier surveys). The completed ACDC system will assist mine countermeasures (MCM) warfighters to more quickly and reliably identify minelike contacts in sidescan, thereby reducing warfighter fatigue, reducing risk to the warfighter, and shortening timelines for completion of MCM objectives. ACDC consists of five major components: (1) clutter detection, (2) feature completion/ classification, (3) geospatial searching, (4) clustering, and (5) scene matching. Depending on the quality of sidescan imagery to be analyzed, each of these steps can be performed autonomously (i.e., with no human intervention) or as a computer-assisted function (in which ACDC suggests statistically likely outcomes to the operator, who makes a final determination).

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2005
Accession Number
ADA494240

Entities

People

  • G. J. Layne
  • M. C. Lohrenz
  • M. L. Gendron

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Algorithms
  • Change Detection
  • Classification
  • Clustering
  • Coordinate Systems
  • Databases
  • Detection
  • Earth Sciences
  • Global Positioning Systems
  • Gray Scale
  • Information Operations
  • Information Systems
  • Military Research
  • Neural Networks
  • Two Dimensional

Readers

  • Coastal Oceanography
  • Computer Vision.
  • Distributed Systems and Data Platform Development