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		<citationkey>RittnerFlorLotu:2007:TeMoGr</citationkey>
		<author>Rittner, Leticia,</author>
		<author>Flores, Franklin,</author>
		<author>Lotufo, Roberto,</author>
		<affiliation>Faculdade de Engenharia Elétrica e de Computação - UNICAMP</affiliation>
		<affiliation>Faculdade de Engenharia Elétrica e de Computação - UNICAMP</affiliation>
		<affiliation>Faculdade de Engenharia Elétrica e de Computação - UNICAMP</affiliation>
		<title>New tensorial representation of color images: tensorial morphological gradient applied to color image segmentation</title>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI)</conferencename>
		<year>2007</year>
		<editor>Falcão, Alexandre Xavier,</editor>
		<editor>Lopes, Hélio Côrtes Vieira,</editor>
		<booktitle>Proceedings</booktitle>
		<date>Oct. 7-10, 2007</date>
		<publisheraddress>Los Alamitos</publisheraddress>
		<publisher>IEEE Computer Society</publisher>
		<conferencelocation>Belo Horizonte</conferencelocation>
		<keywords>color image segmentation, color gradient, watershed transform.</keywords>
		<abstract>This paper proposes a new Tensorial Representation of HSI color images, where each pixel is a 2 X 2 second order tensor, that can be represented by an ellipse. A proposed tensorial morphological gradient (TMG) is defined as the maximum dissimilarity over the neighborhood determined by a structuring element, and is used in the watershed segmentation framework. Many tensor dissimilarity functions are tested and other color gradients are compared. The comparison uses a new methodology for qualitative evaluation of color image segmentation by watershed, where the watershed lines of the n most significant regions are overlaid on the original image for visual comparison. Experiments show that the TMG using Frobenius norm dissimilarity function presents superior segmentation results, in comparison to other tested gradients.</abstract>
		<language>en</language>
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