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Type: Artigo de evento
Title: Graph Cut And Image Segmentation Using Mean Cut By Means Of An Agglomerative Algorithm
Author: Chiba E.A.
De Carvalho M.A.G.
Da Costa A.L.
Abstract: Graph partitioning, or graph cut, has been studied by several authors as a tool for image segmentation. It refers to partitioning a graph into several subgraphs such that each of them represents a meaningful object of interest in the image. In this work we propose a hierarchical agglomerative clustering algorithm driven by the cut and mean cut criteria. Some preliminary experiments were performed using the benchmark of Berkeley BSDS500 with promising results. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.
Editor: SciTePress
Rights: fechado
Identifier DOI: 
Date Issue: 2014
Appears in Collections:Unicamp - Artigos e Outros Documentos

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