GRAPHICAL-DATA-PROCESSING RESEARCH STUDY AND EXPERIMENTAL INVESTIGATION

Abstract

The report describes the continuing development of scanning, preprocessing, character-classification, and context-analysis techniques for hand-printed text, such as computer coding sheets in the FORTRAN language. The performance of topological feature extraction, combined with character classification by a learning machine, is described, and compared with the performance of other combinations. By performing intra-author testing (gathering the training data and test data from the same author), we have achieved a dramatic reduction in test error rate, to less than 10 percent on a limited sample. We describe an experiment in which a fragment of FORTRAN text is scanned, pre-processed, classified character by character, and subjected to context analysis to greatly reduce the recognition-error rate. Finally, we discuss advances in the method of analyzing arithmetic expressions, a key aspect of the context analysis.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1967
Accession Number
AD0661309

Entities

People

  • John H. Munson
  • Peter E. Hart

Organizations

  • SRI International

Tags

Communities of Interest

  • Advanced Electronics

DTIC Thesaurus Topics

  • Adaptive Systems
  • Character Recognition
  • Computer Programming
  • Computers
  • Data Processing
  • Databases
  • Dynamic Programming
  • Extraction
  • Feature Extraction
  • Iterations
  • Language
  • Learning Machines
  • Pattern Recognition
  • Preprocessing
  • Recognition
  • Simulations
  • Test Sets

Fields of Study

  • Computer science

Readers

  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Computer Vision.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation