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Edge detection in contaminated images, using cluster analysis

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Autor dc.contributor.author Allende H.
Autor dc.contributor.author Galbiati J.
Fecha Ingreso dc.date.accessioned 2014-04-05T00:15:25Z
Fecha Disponible dc.date.available 2014-04-05T00:15:25Z
Fecha en Repositorio dc.date.issued 2014-04-04
dc.identifier 10.1007/11578079_97
dc.description.abstract In this paper we present; a method to detect edges in images. The method consists of using a 3×3 pixel mask to scan the image, moving it from left to right and from top to bottom, one pixel at a time. Each time it is placed on the image, an agglomerative hierarchical cluster analysis is applied to the eight outer pixels, When there is more than one cluster, it means that window is on an edge, and the central pixel is marked as an edge point, After scanning all the image, we obtain a new image showing the marked pixels around the existing edges of the image. Then a thinning algorithm is applied so that the edges are well defined, The method results to be particularly efficient when the image is contaminated. In those cases, a previous restoration method is applied, © Springer-Verlag Barlin Heidelberg 2005. en_US
dc.source Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Link Descarga dc.source.uri http://www.scopus.com/inward/record.url?eid=2-s2.0-33745415272&partnerID=40&md5=73592b6530eb88d37b486f400bf29d4b
Title dc.title Edge detection in contaminated images, using cluster analysis en_US
Tipo dc.type Conference Paper
dc.description.keywords Contaminated images; Hierarchical cluster analysis; Algorithms; Hierarchical systems; Image analysis; Restoration; Scanning; Edge detection en_US


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