Integrating neural networks and correlation for identifying targeted control points

Authors

  • ROMUALDO WANDRESEN
  • JOSÉ BITTENCOURT DE ANDRADE
  • EDSON APARECIDO MITISHITA

DOI:

https://doi.org/10.5380/bcg.v11i2.4394

Keywords:

redes neurais artificiais, correlação estatística, pontos pré-sinalizados, identificação automática, morfologia matemática, artificial neural networks, statistical correlation, target, automatic identification, mathematical morphology

Abstract

The main goal of this work is to present new tools for automated identification of photographic images of ground targets for aerophotogrametry applications such as aerotriangulation. The identification of the targeted control points images was done by using the concepts of statistical correlation, artificial neural networks and mathematic morphology with emphasis on binary erosion. It was established procedures for identifying automatically common points in a pair of photographs. With the purpose of verifying the consistency of the identified points a fotogrammetric model of the test area was mounted.

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How to Cite

WANDRESEN, R., DE ANDRADE, J. B., & MITISHITA, E. A. (2005). Integrating neural networks and correlation for identifying targeted control points. Bulletin of Geodetic Sciences, 11(2). https://doi.org/10.5380/bcg.v11i2.4394

Issue

Vol. 11 No. 2 (2005)

Section

Article

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