Theory and Applications of Image Pattern Recognition.

Abstract

In recent years, there has been increasingly great demand for automatic recognition of imagery patterns which arise in biomedical, space, military, security and vast number of other applications. As the computer hardware cost decreases rapidly, automatic image recognition will soon become a reality in many of these applications. Automatic image recognition is also a major step toward designing intelligent machines. In this report, a unified theory of image pattern recognition is developed which includes pattern representation, preprocessing, feature extraction and pattern classification. Computer results from aerial photograph studies are used for illustrative purposes. The theory should be useful for a wide range of imagery patterns. The problem of computational complexity which should be the primary consideration in recognition system design is carefully examined. As the imagery patterns are complicated in nature, it is recommended that both statistical and syntactic methods in pattern recognition should be used to arrive at the best solution for the specific recognition task at hand. Extensive bibliography at the end of the report provides a fairly complete view of the past efforts, approaches and applications of image pattern recognition.

Document Details

Document Type
Technical Report
Publication Date
Feb 24, 1975
Accession Number
ADA011675

Entities

People

  • Chia‐Hung Chen

Organizations

  • University of Massachusetts Dartmouth

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Aerial Photographs
  • Automatic
  • Computational Complexity
  • Computers
  • Feature Extraction
  • Image Recognition
  • Images
  • Pattern Recognition
  • Photographic Materials
  • Photographs
  • Photography
  • Recognition

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • Biotechnology
  • Space