Machine Segmentation of Unformatted Characters.

Abstract

This thesis presents a method of segmenting unformatted alpha-numeric characters. Reconstructing the magnitude of the Fourier transform of a template character with the phase of a string of unformatted characters containing the template character causes all characters that do not have the magnitude of the template to be attenuated in the visual domain. The template character will not be attenuated, since it has both proper magnitude and phase, and a peak detector can find the most probable location of the character. This process also gives a first choice for what the character is (the template). Results are presented for most of the English alphabet. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1981
Accession Number
ADA115556

Entities

People

  • Robin A. Simmons

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Character Recognition
  • Complex Numbers
  • Computations
  • Computers
  • Data Processing
  • Discrete Fourier Transforms
  • Electrical Engineering
  • Fourier Transformation
  • Frequency
  • Frequency Domain
  • Gray Scale
  • Numbers
  • Pattern Recognition
  • Signal Processing
  • Software Development
  • Two Dimensional

Readers

  • Computational Linguistics
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Spectroscopy.