Image retrieval system based in computacional theory perceptions and fuzzy formal language

Orientador: Fernando Antônio Campos GomideDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Neste trabalho utilizam-se as teorias de Linguagem Formal Nebulosa e da Computacional das Percepções de Zadeh para definir buscas em uma base de dados gráfica. A descrição dos elementos gráficos a serem identificados é codificada por meio de sentenças aceitas por uma gramática nebulosa e definida sobre um conjunto de símbolos gráficos terminais reconhecidos por rotinas computacionais específicas. Esses símbolos terminais rotulam a imagem a ser pesquisada. A teoria da Percepção Computacional é usada para permitir que o usuário defina as relações espaciais a serem partilhadas pelos elementos gráficos na cena a ser pesquisada. Os resultados obtidos com buscas realizadas em uma base de dados gráfica com 22000 desenhos mostram que o sistema proposto fornece uma alternativa interessante para solução de buscas em bancos de dados visuaisAbstract: In this work, Fuzzy Formal Language techniques and Zadeh's Computational Theory of Perceptions are used to allow the user to query graphic data bases. The description of the graphic elements to be searched is encoded by means of fuzzy sentences accepted by a fuzzy grammar defined over a set of graphic primitives recognized by specific computational routines aimed to label different primitive graphic components of a given image. The Computational Theory of Perceptions is used to allow the user to specify the required spatial relations to be shared by the selected in the graphic scenes to be selected. The results obtained by querying a 22000 graphic scene data base support the claim that our approach provides a interesting solution for querying visual data basesMestradoEngenharia de ComputaçãoMestre em Engenharia Elétric

Vision artificielle pour les non-voyants : une approche bio-inspirée pour la reconnaissance de formes

More than 315 million people worldwide suffer from visual impairments, with several studies suggesting that this number will double by 2030 due to the ageing of the population. To compensate for the loss of sight the current approaches consist of either specific aids designed to answer particular needs or generic systems such as neuroprostheses and sensory substitution devices. These holistic approaches, which try to restore vision as a whole, have been shown to be very inefficient in real life situations given the low resolution of output interfaces. To overcome these obstacles we propose the use of artificial vision in order to pre-process visual scenes and provide the user with relevant information. We have validated this approach through the development of a novel assistive device for the blind called Navig. Through shape recognition and spatialized sounds synthesis, this system allows users to locate and grab objects of interest. It also features navigational aids based on a new positioning method combining GPS, inertial sensors and the visual detection of geolocalized landmarks. To enhance the performance of the visual module we further developed, as part of this thesis, a bio-inspired pattern recognition algorithm which uses latency-based coding of visual information, oriented edge representations and a cascaded architecture combining detection at different resolutions.La déficience visuelle touche aujourd’hui plus de 315 millions de personnes à travers le monde, un chiffre qui pourrait doubler d’ici à 2030 du fait du vieillissement de la population. Les deux grandes approches existantes pour compenser la perte de vision sont les aides spécifiques, répondant à un besoin identifié, et les systèmes génériques tels que les neuroprothèses ou les systèmes de substitution sensorielle. Ces approches holistiques, tentant de restituer l’ensemble de l’information visuelle, s’avèrent inadaptées de par la trop faible résolution des interfaces de sortie, rendant ces systèmes inutilisables dans la vie quotidienne. Face à ce constat, nous proposons dans cette thèse une démarche alternative, consistant à intégrer des méthodes de vision artificielle, afin de prétraiter la scène visuelle, et de ne restituer au non-voyant que les informations extraites pertinentes. Pour valider cette approche, nous présenterons le développement d’un système de suppléance baptisé Navig. Grâce à la reconnaissance de formes et à la synthèse de sons spatialisés, il permet à l’utilisateur de localiser des objets d’intérêt. Il offre également des fonctions de navigation, basées sur une nouvelle méthode de positionnement combinant GPS, données inertielles, et détections de cibles visuelles géolocalisées. Afin d’améliorer les performances du module de vision artificielle, nous proposerons également dans cette thèse un nouvel algorithme de reconnaissance de formes bio-inspiré, reposant sur un codage de l’information visuelle par latence, sur des représentations sous forme d’arêtes orientées, et sur une architecture en cascade combinant des détections à différentes résolutions