A new approach to image segmentation with two-dimensional hidden Markov models
Image segmentation is one of the fundamental problems in computer vision. In this work, we present a new segmentation algorithm that is based on the theory of twodimensional hidden Markov models (2D-HMM). Unlike most 2DHMM approaches we do not apply the Viterbi Algorithm, instead we present a com...
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Autores principales: | , , , |
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Formato: | conferenceObject |
Lenguaje: | Inglés |
Publicado: |
2021
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Acceso en línea: | http://hdl.handle.net/11086/21146 |
Aporte de: |
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I10-R14111086-21146 |
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institution |
Universidad Nacional de Córdoba |
institution_str |
I-10 |
repository_str |
R-141 |
collection |
Repositorio Digital Universitario (UNC) |
language |
Inglés |
topic |
Classification Agriculture Markov Models Hidden Markov chains |
spellingShingle |
Classification Agriculture Markov Models Hidden Markov chains Baumgartner, Josef Flesia, Ana Georgina Gimenez, Javier Pucheta, Julian A new approach to image segmentation with two-dimensional hidden Markov models |
topic_facet |
Classification Agriculture Markov Models Hidden Markov chains |
description |
Image segmentation is one of the fundamental
problems in computer vision. In this work, we present a new
segmentation algorithm that is based on the theory of twodimensional hidden Markov models (2D-HMM). Unlike most 2DHMM approaches we do not apply the Viterbi Algorithm, instead
we present a computationally efficient algorithm that propagates
the state probabilities through the image. This approach can
easily be extended to higher dimensions. We compare the proposed method with a 2D-HMM standard algorithm and Iterated
Conditional Modes using real world images like a radiography
or a satellite image as well as synthetic images. The experimental
results show that our approach is highly capable of condensing
image segments. This gives our algorithm a significant advantage
over the standard algorithm when dealing with noisy images with
few classes. |
format |
conferenceObject |
author |
Baumgartner, Josef Flesia, Ana Georgina Gimenez, Javier Pucheta, Julian |
author_facet |
Baumgartner, Josef Flesia, Ana Georgina Gimenez, Javier Pucheta, Julian |
author_sort |
Baumgartner, Josef |
title |
A new approach to image segmentation with two-dimensional hidden Markov models |
title_short |
A new approach to image segmentation with two-dimensional hidden Markov models |
title_full |
A new approach to image segmentation with two-dimensional hidden Markov models |
title_fullStr |
A new approach to image segmentation with two-dimensional hidden Markov models |
title_full_unstemmed |
A new approach to image segmentation with two-dimensional hidden Markov models |
title_sort |
new approach to image segmentation with two-dimensional hidden markov models |
publishDate |
2021 |
url |
http://hdl.handle.net/11086/21146 |
work_keys_str_mv |
AT baumgartnerjosef anewapproachtoimagesegmentationwithtwodimensionalhiddenmarkovmodels AT flesiaanageorgina anewapproachtoimagesegmentationwithtwodimensionalhiddenmarkovmodels AT gimenezjavier anewapproachtoimagesegmentationwithtwodimensionalhiddenmarkovmodels AT puchetajulian anewapproachtoimagesegmentationwithtwodimensionalhiddenmarkovmodels AT baumgartnerjosef newapproachtoimagesegmentationwithtwodimensionalhiddenmarkovmodels AT flesiaanageorgina newapproachtoimagesegmentationwithtwodimensionalhiddenmarkovmodels AT gimenezjavier newapproachtoimagesegmentationwithtwodimensionalhiddenmarkovmodels AT puchetajulian newapproachtoimagesegmentationwithtwodimensionalhiddenmarkovmodels |
bdutipo_str |
Repositorios |
_version_ |
1764820395035197442 |