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A Method for Segmentation of Agricultural Fields on Aerial Images with Markov Random Field Model

  • Jamal BouchtiEmail author
  • Adel Asselman
  • Abdellah El Hajjaji
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 911)

Abstract

Aerial imaging has become important to areas like remote sensing, surveying, and particularly in the agricultural application areas. In this paper, we suggest an aerial image segmentation approach based on Markov random field model and Gibbs distributions, we introduce iterative algorithm process to minimize an energy function which incorporate a local characteristics of pixel like color and also Neighborhood characteristics like texture and CIEDE2000.

Keywords

Aerial image segmentation Markov random field Gibbs distribution Potential energy function Iterative algorithm CIEDE2000 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Optique and Photonic Team, Faculty of SciencesM’hannech IITetuanMorocco
  2. 2.Systems of Communications and Detection Laboratory, Faculty of SciencesM’hannech IITetuanMorocco

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