Matching Linear Features of Images and Maps,

Abstract

We present two methods to solve the problem of matching linear features extracted from an aerial image with a set of linear features derived from a map or another view of the same scene. The first method, using discrete relaxation, is very efficient but requires the model to have a small number of elements. The other one, called the kernel method, demonstrates how drastically we can improve the running time if we know a few pairs of matched elements. Illustrative examples are provided, and extensions are discussed. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1982
Accession Number
ADP000116

Entities

People

  • Gerard G. Medioni

Organizations

  • University of Southern California

Tags

DTIC Thesaurus Topics

  • Workshops

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms