Skip to Main content Skip to Navigation
New interface
Conference papers

Markov Models and Extensions for Land Cover Mapping in Aerial Imagery

Abstract : Markov models are well-established stochastic models for image analysis and processing since they allow one to take into account the contextual relationships between image pixels. In this paper, we attempt to methodically review the use of Markov models and their extensions for Land Cover mapping problem in aerial imagery according to available literature and previous research works. A new Markov model combining Markov random fields and hidden Markov models and inspired from the NSHP-HMM model, initially introduced for Handwritten Words Recognition is defined. New learning and labeling procedures are derived.
Complete list of metadata

Cited literature [16 references]  Display  Hide  Download
Contributor : Abdel Belaid Connect in order to contact the contributor
Submitted on : Monday, December 15, 2008 - 10:30:34 AM
Last modification on : Friday, August 5, 2022 - 2:54:44 PM
Long-term archiving on: : Tuesday, June 8, 2010 - 4:06:17 PM


Files produced by the author(s)


  • HAL Id : inria-00346632, version 1



Mohamed El Yazid Boudaren, Abdel Belaïd. Markov Models and Extensions for Land Cover Mapping in Aerial Imagery. International Conference of Signal and Image Engineering - ICSIE 2009, Jul 2009, London, United Kingdom. ⟨inria-00346632⟩



Record views


Files downloads