dc.creatorGutiérrez Mata, Osvaldo
dc.creatorDe la Rosa Vargas, José Ismael
dc.creatorVilla Hernández, José de Jesús
dc.creatorGonzález Elías, Efrén
dc.creatorEscalante, Nivia
dc.date.accessioned2020-05-02T15:19:34Z
dc.date.accessioned2022-10-14T15:16:05Z
dc.date.available2020-05-02T15:19:34Z
dc.date.available2022-10-14T15:16:05Z
dc.date.created2020-05-02T15:19:34Z
dc.date.issued2011-10
dc.identifierhttp://ricaxcan.uaz.edu.mx/jspui/handle/20.500.11845/1864
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4248454
dc.description.abstractIn this work, a novel model of Markov random field is presented, named Semi-Huber potential function, applied to image segmentation in presence of noise. The main difference with respect to other models that have been taken as a reference, is that the number of parameters in the proposed model is significatively smaller. The idea is to choose adequate parameter values heuristically for a good segmentation of the image. In that sense, experiment results show that the proposed model allows a faster and easier parameter adjustment with razonable computation times.
dc.languageeng
dc.publisherCentro de Investigación en Matemáticas, A.C.
dc.relationgeneralPublic
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/3.0/us/
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Estados Unidos de América
dc.sourceVIII Taller-Escuela de Procesamiento de Imágenes - CIMAT, Guanajuato, Guanajuato, Octubre de 2011 (Memorias en CD).
dc.titleSemi-Huber potential function for image segmentation
dc.typeActas de congresos


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