Universidade
Federal do Rio Grande
  • Alto contraste



 

C3 - Artigos Publicados em Periódicos

URI permanente para esta coleçãohttps://rihomolog.furg.br/handle/1/486

Navegar

Filtros

2009 - 200912010 - 20153

Configurações

Tem arquivos: SimAssunto: search.filters.subject.Computer vision

Resultados da Pesquisa

Agora exibindo 1 - 4 de 4
  • Imagem de Miniatura
    Item
    Interactive modeling and evaluation of tumor growth
    (2010) Scharcanski, Jacob; Silva, Luciano Silva da; Koff, David; Wong, Alexander
    This paper addresses the need to quantify tumor growth and detect changes as this information is relevant to manage the patient treatment and to aid biotechnological efforts to cure cancer (Silva et al. 2008). An interactive tumor segmentation technique is used to recover the shape and size of tumors without imposing shape constraints. This segmentation algorithm provides good convergence, is robust to the initialization conditions, and requires simple and intuitive user interactions. A parametric approach to model tumor growth analytically is proposed in this paper. The preliminary experimental results are encouraging. The segmentation method is shown to be robust and simple to use, even in situations where the tumor boundary definition is challenging. Also, the experiments indicate that the proposed model potentially can be used to extrapolate the available data and help predict the tumor size (assuming unconstrained growth). Additionally, the proposed method potentially can provide a quantitative reference to compare the tumor shrinkage rate in cancer treatments.
  • Imagem de Miniatura
    Item
    Automatic control of a ROV for inspection of underwater structures using a low-cost sensing
    (2015) Kuhn, Vinicius Nizolli; Drews Junior, Paulo Lilles Jorge; Gomes, Sebastião Cícero Pinheiro; Cunha, Mauro André Barbosa; Botelho, Silvia Silva da Costa
    This work deals with the implementation of a position and orientation automatic control of an underwater vehicle to perform inspection tasks of submerged structures without using the knowledge of a previous dynamic model in the control law and, mainly, by using a low-cost embedded minimal instrumentation. This instrumentation does not employ expensive components to determine the position and orientation of the vehicle, like a central inertial. In this way, a computer vision system is used as a sensory source in order to assist the control. It was developed an algorithm to image processing and a system for integrating the different sensors. Experimental results using the proposed sensing show that the closed-loop control of the vehicle was suitable for the conduction of inspections.
  • Imagem de Miniatura
    Item
    Controlling a system for underwater visual inspection
    (2013) Drews Junior, Paulo Lilles Jorge; Kuhn, Vinicius Nizolli; Gomes, Sebastião Cícero Pinheiro
    Nowadays, the ocean plays a fundamental role in the global economy, mainly due to oil extraction industry. It makes the environment be populated with human-made structures that needs to be inspected and maintained. In this context, this paper details a system for online detect an underwater cable-like target using computer vision algorithms, as well as an automatic control of a vehicle to tracking it. This system could be used to assist a human operator during visual inspection tasks. This work is concluded with a series of tests and analyses aiming to the system validation.
  • Imagem de Miniatura
    Item
    Appearance-based odometry and mapping with feature descriptors for underwater robots
    (2009) Botelho, Silvia Silva da Costa; Drews Junior, Paulo Lilles Jorge; Figueiredo, Mônica da Silva; Rocha, Celina Haffele da; Oliveira, Gabriel Leivas
    The use of Autonomous Underwater Vehicles (AUVs) for underwater tasks is a promising robotic field. These robots can carry visual inspection cameras. Besides serving the activities of inspection and mapping, the captured images can also be used to aid navigation and localization of the robots. Visual odometry is the process of determining the position and orientation of a robot by analyzing the associated camera images. It has been used in a wide variety of non-standard locomotion robotic methods. In this context, this paper proposes an approach to visual odometry and mapping of underwater vehicles. Supposing the use of inspection cameras, this proposal is composed of two stages: i) the use of computer vision for visual odometry, extracting landmarks in underwater image sequences and ii) the development of topological maps for localization and navigation. The integration of such systems will allow visual odometry, localization and mapping of the environment. A set of tests with real robots was accomplished, regarding online and performance issues. The results reveals an accuracy and robust approach to several underwater conditions, as illumination and noise, leading to a promissory and original visual odometry and mapping technique.