INVESTIGADORES
FLESIA Ana Georgina
congresos y reuniones científicas
Título:
On segmentation with Markovian models.
Autor/es:
ANA GEORGINA FLESIA; JAVIER GIMENEZ; JOSEPH BAUMGARTNER
Lugar:
Córdoba
Reunión:
Simposio; ASAI 2013; 2013
Institución organizadora:
SADIO
Resumen:
This paper addresses the image modeling problem under the
assumption that images can be represented by 2d order, hidden Markov
random fields models. The modeling applications we have in mind com-
prise pixelwise segmentation of gray-level images coming from the field
of Oral Radiographic Differential Diagnosis. Segmentation is achieved
by approximations to the solution of the maximum a posteriori equation
(MAP) when the emission distribution is assumed the same in all models
and the difference lays in the Neighborhood Markovian hypothesis made
over the labeling random field. For two algorithms, 2d path-constrained
Viterbi training and Potts-ICM we investigate goodness of fit by study-
ing statistical complexity, computational gain, extent of automation, and
rate of classification measured with kappa statistic. All code written is
provided in a Matlab toolbox available for download from our website,
following the Reproducible Research Paradigm.