Parsing Intensity Profiles,

Abstract

Much low-level vision work in (artificial intelligence) deals with one-dimensional intensity profiles. This paper describes PROPAR, a system that allows a convenient and uniform mechanism for recognizing such profiles. PROPAR is a modified Augmented Transition Networks parser. The grammar used by the parser serves to describe and label the set of acceptable profiles. The input to the parser are descriptions of segments of a piecewise linear approximation to an intensity profile. A sample grammar is presented and the results discussed. (Author)

Document Details

Document Type
Technical Report
Publication Date
May 01, 1975
Accession Number
ADA021172

Entities

People

  • Tomas Lozano-Pérez

Organizations

  • Massachusetts Institute of Technology

Tags

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Intensity
  • Transitions

Readers

  • Computational Linguistics
  • Computer Vision.
  • Fluid Dynamics.

Technology Areas

  • AI & ML
  • AI & ML - Information Retrieval
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Machine Translation