Real time image segmentation using an adaptive thresholding approach

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dc.contributorInformática Industrial e Inteligencia Artificial-
dc.contributor.authorArques Corrales, Pilar-
dc.contributor.authorAznar Gregori, Fidel-
dc.contributor.authorPujol, Mar-
dc.contributor.authorRizo, Ramón-
dc.contributor.otherUniversidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial-
dc.identifier.citationARQUES CORRALES, Pilar, et al. “Real time image segmentation using an adaptive thresholding approach”. Lecture notes in computer science. 2006, vol. 4177/2006. ISSN 0302-9743, pp. 389-398en
dc.description.abstractThe aim of image segmentation is the partition of the image in homogeneous regions. In this paper we propose an approximation based on Markov Random Fields (MRF) able to perform correct segmentation in real time using colour information. In a first approximation a simulated annealing approach is used to obtain the optimal segmentation. This segmentation will be improved using an adaptive threshold algorithm, to achieve real time. The experiment results using the proposed segmentation prove its correctness, both for the obtained labelling and for the response time.en
dc.description.sponsorshipProyecto de la Generalitat Valenciana GV04B685en
dc.rightsThe original publication is available at www.springerlink.comen
dc.subjectRegion segmentationen
dc.subjectAdaptive thresholdingen
dc.subjectSimulated annealingen
dc.subjectReal timeen
dc.subjectMarkov Random Fielden
dc.subject.otherCiencia de la Computación e Inteligencia Artificialen
dc.titleReal time image segmentation using an adaptive thresholding approachen
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