Generalized Hough Transform for Object Classification in the Maritime Domain

Abstract

A Generalized Hough Transform (GHT)-based classification scheme for an object-of-interest in maritime-domain images is proposed in this thesis. First, the object edge points are extracted and used to generate a representation of the object as a Hough coordinate table by using the GHT algorithm. The table is then reformatted to a contour map called a Hough features map. The coordinates of dominant peaks or Hough features on the map are extracted and fed into a feed-forward, back-propagation neural network for classification. In this research, the scheme is tested using perfect shapes of triangles, squares, circles, andstars and maritime-domain images of ships, aircraft, and clouds, and the classification results obtained are reported.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2015
Accession Number
AD1009203

Entities

People

  • Pornrerk Rerkngamsanga

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Space

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Change Detection
  • Computer Science
  • Computer Vision
  • Computers
  • Detection
  • Detectors
  • Electrical Engineering
  • Feature Extraction
  • Image Processing
  • Machine Learning
  • Neural Networks
  • Pattern Recognition
  • Signal Processing
  • Two Dimensional
  • United States Naval Academy

Readers

  • Approximation Theory.
  • Computer Vision.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks