dc.contributor.author | Baumgartner, Josef | |
dc.contributor.author | Flesia, Ana Georgina | |
dc.contributor.author | Gimenez, Javier | |
dc.contributor.author | Pucheta, Julian | |
dc.date.accessioned | 2021-11-03T18:02:40Z | |
dc.date.available | 2021-11-03T18:02:40Z | |
dc.date.issued | 2013 | |
dc.identifier.uri | http://hdl.handle.net/11086/21146 | |
dc.description.abstract | 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. | es |
dc.format.medium | Electrónico y/o Digital | |
dc.language.iso | eng | es |
dc.rights | Attribution-NonCommercial-ShareAlike 4.0 International | * |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-sa/4.0/ | * |
dc.subject | Classification | es |
dc.subject | Agriculture | es |
dc.subject | Markov Models | es |
dc.subject | Hidden Markov chains | es |
dc.title | A new approach to image segmentation with two-dimensional hidden Markov models | es |
dc.type | conferenceObject | es |
dc.description.fil | Fil: Baumgartner, Josef. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. | es |
dc.description.fil | Fil: Flesia, Ana Georgina. Universidad Tecnológica Nacional; Argentina. | es |
dc.description.fil | Fil: Flesia, Ana Georgina. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. | es |
dc.description.fil | Fil: Flesia, Ana Georgina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. | es |
dc.description.fil | Fil: Gimenez, Javier. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. | es |
dc.description.fil | Fil: Pucheta, Julián. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. | es |
dc.description.field | Sistemas de Automatización y Control | |
dc.conference.city | Recife | |
dc.conference.country | Brasil | |
dc.conference.editorial | Recife | |
dc.conference.event | 1st BRICS Countries Congress (BRICS-CCI) and 11th Brazilian Congress (CBIC) on Computational Intelligence | |
dc.conference.eventcity | Recife | |
dc.conference.eventcountry | Brasil | |
dc.conference.eventdate | 2013-9 | |
dc.conference.institution | IEEE | |
dc.conference.journal | Anales del BRICS | |
dc.conference.publication | Libro | |
dc.conference.work | Artículo Completo | |
dc.conference.type | Congreso | |