{"id":64095,"date":"2018-03-09T22:52:04","date_gmt":"2018-03-09T22:52:04","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/reconocimiento-de-imagenes-de-color-y-textura-mediante-una-arquitectura-neuronal-multi-escala-inspirada-en-las-areas-visuales-del-sistema-humano-con-filtrado-orientacional-y-difusion-cromatica\/"},"modified":"2018-03-09T22:52:04","modified_gmt":"2018-03-09T22:52:04","slug":"reconocimiento-de-imagenes-de-color-y-textura-mediante-una-arquitectura-neuronal-multi-escala-inspirada-en-las-areas-visuales-del-sistema-humano-con-filtrado-orientacional-y-difusion-cromatica","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/vision-artificial\/reconocimiento-de-imagenes-de-color-y-textura-mediante-una-arquitectura-neuronal-multi-escala-inspirada-en-las-areas-visuales-del-sistema-humano-con-filtrado-orientacional-y-difusion-cromatica\/","title":{"rendered":"Reconocimiento de im\u00e1genes de color y textura mediante una arquitectura neuronal multi-escala inspirada en las \u00e1reas visuales del sistema humano con filtrado orientacional y difusi\u00f3n crom\u00e1tica"},"content":{"rendered":"<h2>Tesis doctoral de <strong> M\u00edriam Ant\u00f3n Rodr\u00edguez <\/strong><\/h2>\n<p>El objetivo de esta tesis es desarrollar un modelo neuronal multi-escala para el reconocimiento de im\u00e1genes en color de escenas texturadas. El modelo, que combina informaci\u00f3n crom\u00e1tica y textural para segmentar y reconocer las im\u00e1genes de forma coherente, est\u00e1 constitu\u00eddo por dos m\u00f3dulos principales: el m\u00f3dulo de segmentaci\u00f3n compuesto por el sistema de color oponente (colour opponent system, cos) y el sistema de segmentaci\u00f3n crom\u00e1tica (chromatic sementation system,css); y el m\u00f3dulo de reconocimiento basado en una red neuronal artmap con propiedades de invarianza en escala y en orientaci\u00f3n. La segmentaci\u00f3n se realiza mediante la extracci\u00f3n de contornos perceptuales y procesos de difusi\u00f3n sobre los canales oponentes crom\u00e1ticos, basados en la teor\u00eda psicof\u00edsica humana de la percepci\u00f3n del color. El m\u00f3dulo css lleva a cabo los procesos de realzado de las regiones de color mediante un bucle multi-escalas de filtros orientados y mecanismos de competici\u00f3n-cooperaci\u00f3n. Las salidas de estos realzados, junto con las caracter\u00edsticas locales de la textura constituyen el patr\u00f3n de entrada al clasificador neuronal supervisado. Posteriormente, la etapa neuronal realiza un reconocimiento atentivo de la escena mediante la respuesta de filtros orientados y difusiones crom\u00e1ticas.<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Reconocimiento de im\u00e1genes de color y textura mediante una arquitectura neuronal multi-escala inspirada en las \u00e1reas visuales del sistema humano con filtrado orientacional y difusi\u00f3n crom\u00e1tica<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Reconocimiento de im\u00e1genes de color y textura mediante una arquitectura neuronal multi-escala inspirada en las \u00e1reas visuales del sistema humano con filtrado orientacional y difusi\u00f3n crom\u00e1tica <\/li>\n<li><strong>Autor:<\/strong>\u00a0 M\u00edriam Ant\u00f3n Rodr\u00edguez <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Valladolid<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 21\/04\/2008<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3>Direcci\u00f3n y tribunal<\/h3>\n<ul>\n<li><strong>Director de la tesis<\/strong>\n<ul>\n<li>Jos\u00e9 Fernando D\u00edez Higuera<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: Juan Lopez coronado <\/li>\n<li>Jos\u00e9 Mar\u00eda Sebasti\u00e1n y z\u00fa\u00f1iga (vocal)<\/li>\n<li>Rafael Mompo gomez (vocal)<\/li>\n<li>Luis Pastor p\u00e9rez (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de M\u00edriam Ant\u00f3n Rodr\u00edguez El objetivo de esta tesis es desarrollar un modelo neuronal multi-escala para el reconocimiento [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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