{"id":77166,"date":"2018-03-09T23:22:40","date_gmt":"2018-03-09T23:22:40","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/vlsi-architecture-for-motion-estimation-in-underwater-imaging\/"},"modified":"2018-03-09T23:22:40","modified_gmt":"2018-03-09T23:22:40","slug":"vlsi-architecture-for-motion-estimation-in-underwater-imaging","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/vision-artificial\/vlsi-architecture-for-motion-estimation-in-underwater-imaging\/","title":{"rendered":"Vlsi architecture for motion estimation in underwater imaging"},"content":{"rendered":"<h2>Tesis doctoral de <strong> Simona Ila Viorela <\/strong><\/h2>\n<p>El trabajo desarrollado en esta tesis aporta soluciones innovadoras en el campo del tratamiento de im\u00e1genes submarinas. En este entorno, la tarea de procesamiento de im\u00e1genes es complejo por la falta de contornos bien definidos debido a la borrosidad de las im\u00e1genes, por una parte, y a la necesidad de un sistema de iluminaci\u00f3n artificial que produce una iluminaci\u00f3n no uniforme. la estimaci\u00f3n del movimiento del veh\u00edculo y su localizaci\u00f3n son dos problemas fundamentales en rob\u00f3tica submarina. Una manera de solucionar estos problemas es mediante el uso de un sistema de visi\u00f3n por computador. Los sistemas de visi\u00f3n se caracterizan por su alta resoluci\u00f3n, bajo coste y por el hecho de proporcionar una gran cantidad de informaci\u00f3n. La estimaci\u00f3n del movimiento se hace a partir las correspondencias entre dos im\u00e1genes adquiridas por una c\u00e1mara montada en el veh\u00edculo y orientada hacia el fondo marino. Las correspondencias se pueden obtener utilizando t\u00e9cnicas de \u00abmatching\u00bb. En esta tesis se propone un algoritmo que permite detectar correspondencias entre im\u00e1genes consecutivas en tiempo real. las dos aportaciones principales de esta tesis son, por un lado, un m\u00e9todo que mejora el algoritmo de \u00abmatching\u00bb dot\u00e1ndolo de mayor robusteza, y por otro, la implementaci\u00f3n en hardware del algoritmo con la finalidad de obtener una ejecuci\u00f3n en tiempo real. desde el punto de vista algor\u00edtmico, la tesis propone la utilizaci\u00f3n de caracter\u00edsticas de textura para eliminar falsas correspondencias (denominadas \u00aboutliers\u00bb) entre dos im\u00e1genes mejorando la robustez del algoritmo de \u00abmatching\u00bb y permitiendo mejorar los resultados del algoritmo de estimaci\u00f3n del movimiento que es muy sensitivo a las falsas correspondencias. La t\u00e9cnica propuesta en esta tesis se ha obtenido mediante un amplio estudio con un gran n\u00famero de experimentos para seleccionar el operador de textura m\u00e1s adecuado para el tratamiento de im\u00e1genes submarinas. En comparaci\u00f3n con los m\u00e9todos ya e<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Vlsi architecture for motion estimation in underwater imaging<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Vlsi architecture for motion estimation in underwater imaging <\/li>\n<li><strong>Autor:<\/strong>\u00a0 Simona Ila Viorela <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Girona<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 14\/11\/2005<\/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>Rafael Garcia Campos<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: xavier Cufi <\/li>\n<li>Antonio Benito (vocal)<\/li>\n<li>fran\u00ed\u00a7ois Charot (vocal)<\/li>\n<li>  (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Simona Ila Viorela El trabajo desarrollado en esta tesis aporta soluciones innovadoras en el campo del tratamiento [&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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