DISCOVERY AND LEARNING TECHNIQUES FOR PATTERN RECOGNITION.

Abstract

This paper describes a pattern recognition program which accepts any 20 x 20 black-and-white pattern, reduces it to a one-dimensional description of its contour, and identifies the pattern. Starting without operators or pre-set memory, the program learns via a feedback process, what characterizes each pattern type. It begins its identification of a new pattern by searching for matches between portions of the pattern's contour and learned stroke-like characteristics. A study of locations of certain of these matches, plus a comparison with memory, yields an identification of the pattern. The paper also discusses ideas for future pattern recognizers. (Author)

Document Details

Document Type
Technical Report
Publication Date
Nov 18, 1964
Accession Number
AD0610725

Entities

People

  • Leonard M. Uhr
  • Rebecca C. Prather

Organizations

  • System Development Corporation

Tags

DTIC Thesaurus Topics

  • Feedback
  • Identification
  • Pattern Recognition
  • Recognition

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Computational Modeling and Simulation
  • Computer Vision.

Technology Areas

  • AI & ML