Outdoor Landmark Recognition using Hybrid Fractal Vision System and Neural Networks.

Abstract

A hybrid fractal vision system is being developed for landmark detection and recognition in natural scenes. At the current quarter of research, a reconfigurable neural network is being designed to recognize landmarks. The fractal model detected the landmarks for cluttered images, and the neural network would recognize those landmarks. A brief description of the theoretical design of this Reconfigurable Neural Network is given here. Also, some of the initial results obtained by testing the neural network on real image data are included with this report. A new learning method is also being developed and briefly reported here. Automatic recognition systems can be useful in both military and commercial domains. Tasks such as military surveillance, automatic target recognition, automatic vehicle navigation, material handling, inspection, data compression/decompression, autonomous robot navigation, etc are some of the practical issues directly enhanced by automatic and robust vision systems.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1995
Accession Number
ADA299738

Entities

People

  • Ren C. Luo

Organizations

  • North Carolina State University

Tags

DTIC Thesaurus Topics

  • Automatic
  • Autonomous Navigation
  • Compression
  • Data Compression
  • Decompression
  • Detection
  • Navigation
  • Neural Networks
  • Recognition
  • Robot Navigation
  • Robots
  • Target Recognition

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Neural Networks
  • Autonomy
  • Autonomy - Autonomous System Control