A Support Vector Machine Application on Vehicles

Abstract

In this paper, methods of choosing a vehicle out of an image are explored. Digital images are taken from a monocular camera. Image processing techniques are applied to each single frame picture to create the feature vector. Finally the resulting features are used to classify whether there is a car in the picture or not using support vector machines. The result are compared to those obtained using a neural network. A discussion on techniques to enhance the feature vector and the results from both learning machines will be included.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2001
Accession Number
ADA459231

Entities

People

  • Jack Reed
  • Michael Del Rose

Organizations

  • Tank-automotive and Armaments Command

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Bias
  • Cameras
  • Classification
  • Computing System Architectures
  • Data Sets
  • Digital Cameras
  • Digital Images
  • Image Processing
  • Images
  • Learning Machines
  • Machine Learning
  • Neural Networks
  • Operations Security
  • Pattern Recognition
  • Recognition
  • Supervised Machine Learning

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks