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		<citationkey>Cuadros-VargasGerCasBatNon:2006:Im2DMe</citationkey>
		<author>Cuadros-Vargas, Alex J.,</author>
		<author>Gerhardinger, Leandro C.,</author>
		<author>Castro, Mário,</author>
		<author>Batista Neto, João,</author>
		<author>Nonato, Luis G.,</author>
		<affiliation>ICMC - Instituto de Ciências Matemáticas e de Computação - USP</affiliation>
		<affiliation>ICMC - Instituto de Ciências Matemáticas e de Computação - USP</affiliation>
		<affiliation>ICMC - Instituto de Ciências Matemáticas e de Computaão - USP</affiliation>
		<affiliation>ICMC - Instituto de Ciências Matemáticas e de Computaão - USP</affiliation>
		<affiliation>ICMC - Instituto de Ciências Matemáticas e de Computaão - USP</affiliation>
		<title>Improving 2D mesh image segmentation with Markovian Random Fields</title>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 19 (SIBGRAPI)</conferencename>
		<year>2006</year>
		<editor>Oliveira Neto, Manuel Menezes de,</editor>
		<editor>Carceroni, Rodrigo Lima,</editor>
		<booktitle>Proceedings</booktitle>
		<date>8-11 Oct. 2006</date>
		<publisheraddress>Los Alamitos</publisheraddress>
		<publisher>IEEE Computer Society</publisher>
		<conferencelocation>Manaus</conferencelocation>
		<keywords>Polygonal Meshes, Texture Analysis, Segmentation.</keywords>
		<abstract>Traditional mesh segmentation methods normally operate on geometrical models with no image information. On the other hand, 2D image-based mesh generation and segmentation counterparts, such as Imesh \cite{Vargas:05} perform the task by following a set of well defined rules derived from the geometry of the triangles, but with no statistical information of the mesh elements. This paper presents a novel segmentation method that combines the original Imesh image-based segmentation approach with Markovian Random Field (MRF) models. It takes an image as input, generate a mesh of triangles and, by treating the mesh as a Markovian field, produces quality unsupervised segmentation. The results have demonstrated that the method not only provides better segmentation than that of original Imesh, but is also capable of producing MRF-like segmentation output for certain types of images, with considerable cut in processing times.</abstract>
		<language>en</language>
		<tertiarytype>Full Paper</tertiarytype>
		<format>On-line</format>
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		<targetfile>Vargas-MRF_Mesh.pdf</targetfile>
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		<e-mailaddress>jbatista@icmc.usp.br</e-mailaddress>
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