{"id":499,"date":"2016-07-16T23:31:59","date_gmt":"2016-07-17T02:31:59","guid":{"rendered":"https:\/\/sbia.org.br\/lnlm\/?page_id=499"},"modified":"2016-07-16T23:31:59","modified_gmt":"2016-07-17T02:31:59","slug":"vol8-no4-art1","status":"publish","type":"page","link":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol8-no4\/vol8-no4-art1\/","title":{"rendered":"Avalia\u00e7\u00e3o do M\u00e9todo Dial\u00e9tico na Quantiza\u00e7\u00e3o de Imagens Multiespectrais"},"content":{"rendered":"<p><strong>T\u00edtulo:<\/strong> Avalia\u00e7\u00e3o do M\u00e9todo Dial\u00e9tico na Quantiza\u00e7\u00e3o de Imagens Multiespectrais<\/p>\n<p><strong>Autores:<\/strong> Santos, Wellington Pinheiro dos; Assis, Francisco Marcos de<\/p>\n<p align=\"justify\"><strong>Resumo:<\/strong> A classifica\u00e7\u00e3o n\u00e3o supervisionada tem um papel muito importante na an\u00e1lise de imagens multiespectrais, dada a sua capacidade para auxiliar a extra\u00e7\u00e3o de conhecimento a priori de imagens. Algoritmos como k-m\u00e9dias e fuzzy c-m\u00e9dias tem sido muito utilizados nessa tarefa. A Intelig\u00eancia Computacional tem-se mostrado como um importante campo para auxiliar na constru\u00e7\u00e3o de classificadores otimizados, tanto quanto \u00e0 qualidade do agrupamento de classes, quanto \u00e0 avalia\u00e7\u00e3o da qualidade da quantiza\u00e7\u00e3o vetorial. Diversos trabalhos t\u00eam mostrado que a Filosofia, em especial o M\u00e9todo Dial\u00e9tico, tem servido como importante inspira\u00e7\u00e3o para a constru\u00e7\u00e3o de novos m\u00e9todos computacionais. Este trabalho apresenta uma avalia\u00e7\u00e3o de quatro m\u00e9todos baseados na Dial\u00e9tica: o Classificador Dial\u00e9tico Objetivo e o M\u00e9todo Dial\u00e9tico de Otimiza\u00e7\u00e3o adaptado \u00e0 constru\u00e7\u00e3o de uma vers\u00e3o do k-m\u00e9dias otimizada segundo \u00edndices de qualidade de agrupamento, cada um desses em uma vers\u00e3o can\u00f4nica e em outra vers\u00e3o obtida pela aplica\u00e7\u00e3o do Princ\u00edpio da M\u00e1xima Entropia. Esses m\u00e9todos foram comparados aos m\u00e9todos k-m\u00e9dias, fuzzy c-m\u00e9dias e mapa auto-organizado de Kohonen. Os resultados mostraram que os m\u00e9todos baseados na Dial\u00e9tica s\u00e3o robustos ao ru\u00eddo e podem atingir resultados de quantiza\u00e7\u00e3o t\u00e3o bons quanto aqueles obtidos com o mapa de Kohonen, considerado um quantizador \u00f3timo.<\/p>\n<p><strong>Palavras-chave:<\/strong> Segmenta\u00e7\u00e3o de imagens; k-m\u00e9dias; dial\u00e9tica; otimiza\u00e7\u00e3o; princ\u00edpio da m\u00e1xima entropia; computa\u00e7\u00e3o evolucion\u00e1ria<\/p>\n<p><strong>P\u00e1ginas:<\/strong> 28<\/p>\n<p><strong>C\u00f3digo DOI:<\/strong> <a href=\"http:\/\/dx.doi.org\/10.21528\/lnlm-vol8-no4-art1\">10.21528\/lmln-vol8-no4-art1<\/a><\/p>\n<p><strong>Artigo em PDF:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2016\/07\/vol8-no4-art1.pdf\" rel=\"\">vol8-no4-art1.pdf<\/a><\/p>\n<p><strong>Arquivo BibTex:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2016\/07\/vol8-no4-art1.bib\" rel=\"\">vol8-no4-art1.bib<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>T\u00edtulo: Avalia\u00e7\u00e3o do M\u00e9todo Dial\u00e9tico na Quantiza\u00e7\u00e3o de Imagens Multiespectrais Autores: Santos, Wellington Pinheiro dos; Assis, Francisco Marcos de Resumo: A classifica\u00e7\u00e3o n\u00e3o supervisionada tem um papel muito importante na an\u00e1lise de imagens multiespectrais, dada a sua capacidade para auxiliar <a href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol8-no4\/vol8-no4-art1\/\" class=\"read-more\">Read More &#8230;<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":497,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-499","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Avalia\u00e7\u00e3o do M\u00e9todo Dial\u00e9tico na Quantiza\u00e7\u00e3o de Imagens Multiespectrais - Learning and NonLinear Models<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol8-no4\/vol8-no4-art1\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Avalia\u00e7\u00e3o do M\u00e9todo Dial\u00e9tico na Quantiza\u00e7\u00e3o de Imagens Multiespectrais - Learning and NonLinear Models\" \/>\n<meta property=\"og:description\" content=\"T\u00edtulo: Avalia\u00e7\u00e3o do M\u00e9todo Dial\u00e9tico na Quantiza\u00e7\u00e3o de Imagens Multiespectrais Autores: Santos, Wellington Pinheiro dos; 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