53 resultados para Machine Vision and Image Processing

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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Psychophysical studies suggest that humans preferentially use a narrow band of low spatial frequencies for face recognition. Here we asked whether artificial face recognition systems have an improved recognition performance at the same spatial frequencies as humans. To this end, we estimated recognition performance over a large database of face images by computing three discriminability measures: Fisher Linear Discriminant Analysis, Non-Parametric Discriminant Analysis, and Mutual Information. In order to address frequency dependence, discriminabilities were measured as a function of (filtered) image size. All three measures revealed a maximum at the same image sizes, where the spatial frequency content corresponds to the psychophysical found frequencies. Our results therefore support the notion that the critical band of spatial frequencies for face recognition in humans and machines follows from inherent properties of face images, and that the use of these frequencies is associated with optimal face recognition performance.

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In the context of the round table the following topics related to image colour processing will be discussed: historical point of view. Studies of Aguilonius, Gerritsen, Newton and Maxwell. CIE standard (Commission International de lpsilaEclaraige). Colour models. RGB, HIS, etc. Colour segmentation based on HSI model. Industrial applications. Summary and discussion. At the end, video images showing the robustness of colour in front of B/W images will be presented

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"Vegeu el resum a l'inici del document del fitxer adjunt."

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The increasing volume of data describing humandisease processes and the growing complexity of understanding, managing, and sharing such data presents a huge challenge for clinicians and medical researchers. This paper presents the@neurIST system, which provides an infrastructure for biomedical research while aiding clinical care, by bringing together heterogeneous data and complex processing and computing services. Although @neurIST targets the investigation and treatment of cerebral aneurysms, the system’s architecture is generic enough that it could be adapted to the treatment of other diseases.Innovations in @neurIST include confining the patient data pertaining to aneurysms inside a single environment that offers cliniciansthe tools to analyze and interpret patient data and make use of knowledge-based guidance in planning their treatment. Medicalresearchers gain access to a critical mass of aneurysm related data due to the system’s ability to federate distributed informationsources. A semantically mediated grid infrastructure ensures that both clinicians and researchers are able to seamlessly access andwork on data that is distributed across multiple sites in a secure way in addition to providing computing resources on demand forperforming computationally intensive simulations for treatment planning and research.

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Transmission electron microscopy is a proven technique in the field of cell biology and a very useful tool in biomedical research. Innovation and improvements in equipment together with the introduction of new technology have allowed us to improve our knowledge of biological tissues, to visualizestructures better and both to identify and to locate molecules. Of all the types ofmicroscopy exploited to date, electron microscopy is the one with the mostadvantageous resolution limit and therefore it is a very efficient technique fordeciphering the cell architecture and relating it to function. This chapter aims toprovide an overview of the most important techniques that we can apply to abiological sample, tissue or cells, to observe it with an electron microscope, fromthe most conventional to the latest generation. Processes and concepts aredefined, and the advantages and disadvantages of each technique are assessedalong with the image and information that we can obtain by using each one ofthem.

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Quickremovalofbiosolidsinaquaculturefacilities,andspeciallyinrecirculatingaquaculturesystems(RAS),isoneofthemostimportantstepinwastemanagement.Sedimentationdynamicsofbiosolidsinanaquaculturetankwilldeterminetheiraccumulationatthebottomofthetank.

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La idea del proyecto viene del concepto de “fábricas del futuro”, donde las barreras entre robots y humanos se rompen para que la colaboración entre ambos sea como en un equipo. Para la realización de este proyecto se ha utilizado el brazo robótico IRB120 de la marca ABB de 6 Grados de libertad, Matlab y el software Robot Studio. El Objetivo principal de este proyecto es establecer el protocolo de comunicación trabajador-robot mediante imágenes. El trabajador debería poder controlar el robot mediante dibujos realizados en la mesa de trabajo. En el desarrollo de la comunicación trabajador-robot cabe distinguir tres partes: · El análisis y tratamiento de imágenes para el cual se ha utilizado el software Matlab. · Transmisión de los datos desde Matlab al robot. · Programación de las acciones a realizar por el robot mediante el software “Robot Studio”. Con el protocolo de comunicación desarrollado y las imágenes realizadas por el trabajador el robot es capaz de detectar lo siguiente: · la herramienta que debe utilizar (rotulador, boli o ventosa) · si lo que tiene que dibujar en la mesa de trabajo son puntos o trazo continuo. · la localización de los puntos o del trazo continuo en la mesa de trabajo. Se ha alcanzado el objetivo propuesto con éxito, el protocolo de comunicación trabajador-robot mediante imágenes ha sido establecido. Mediante el análisis y tratamiento de imágenes se puede conseguir la información necesaria para que el robot pueda ejecutar las acciones requeridas por el trabajador.

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In this paper we face the problem of positioning a camera attached to the end-effector of a robotic manipulator so that it gets parallel to a planar object. Such problem has been treated for a long time in visual servoing. Our approach is based on linking to the camera several laser pointers so that its configuration is aimed to produce a suitable set of visual features. The aim of using structured light is not only for easing the image processing and to allow low-textured objects to be treated, but also for producing a control scheme with nice properties like decoupling, stability, well conditioning and good camera trajectory

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En el presente artículo se ha desarrollado un sistema capaz de categorizar de forma automática la base de datos de imágenes que sirven de punto de partida para la ideación y diseño en la producción artística del escultor M. Planas. La metodología utilizada está basada en características locales. Para la construcción de un vocabulario visual se sigue un procedimiento análogo al que se utiliza en el análisis automático de textos (modelo 'Bag-of-Words'-BOW) y en el ámbito de las imágenes nos referiremos a representaciones 'Bag-of-Visual Terms' (BOV). En este enfoque se analizan las imágenes como un conjunto de regiones, describiendo solamente su apariencia e ignorando su estructura espacial. Para superar los inconvenientes de polisemia y sinonimia que lleva asociados esta metodología, se utiliza el análisis probabilístico de aspectos latentes (PLSA) que detecta aspectos subyacentes en las imágenes, patrones formales. Los resultados obtenidos son prometedores y, además de la utilidad intrínseca de la categorización automática de imágenes, este método puede proporcionar al artista un punto de vista auxiliar muy interesante.

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This paper deals with the problem of navigation for an unmanned underwater vehicle (UUV) through image mosaicking. It represents a first step towards a real-time vision-based navigation system for a small-class low-cost UUV. We propose a navigation system composed by: (i) an image mosaicking module which provides velocity estimates; and (ii) an extended Kalman filter based on the hydrodynamic equation of motion, previously identified for this particular UUV. The obtained system is able to estimate the position and velocity of the robot. Moreover, it is able to deal with visual occlusions that usually appear when the sea bottom does not have enough visual features to solve the correspondence problem in a certain area of the trajectory

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It is well known that image processing requires a huge amount of computation, mainly at low level processing where the algorithms are dealing with a great number of data-pixel. One of the solutions to estimate motions involves detection of the correspondences between two images. For normalised correlation criteria, previous experiments shown that the result is not altered in presence of nonuniform illumination. Usually, hardware for motion estimation has been limited to simple correlation criteria. The main goal of this paper is to propose a VLSI architecture for motion estimation using a matching criteria more complex than Sum of Absolute Differences (SAD) criteria. Today hardware devices provide many facilities for the integration of more and more complex designs as well as the possibility to easily communicate with general purpose processors

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Photo-mosaicing techniques have become popular for seafloor mapping in various marine science applications. However, the common methods cannot accurately map regions with high relief and topographical variations. Ortho-mosaicing borrowed from photogrammetry is an alternative technique that enables taking into account the 3-D shape of the terrain. A serious bottleneck is the volume of elevation information that needs to be estimated from the video data, fused, and processed for the generation of a composite ortho-photo that covers a relatively large seafloor area. We present a framework that combines the advantages of dense depth-map and 3-D feature estimation techniques based on visual motion cues. The main goal is to identify and reconstruct certain key terrain feature points that adequately represent the surface with minimal complexity in the form of piecewise planar patches. The proposed implementation utilizes local depth maps for feature selection, while tracking over several views enables 3-D reconstruction by bundle adjustment. Experimental results with synthetic and real data validate the effectiveness of the proposed approach

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In a search for new sensor systems and new methods for underwater vehicle positioning based on visual observation, this paper presents a computer vision system based on coded light projection. 3D information is taken from an underwater scene. This information is used to test obstacle avoidance behaviour. In addition, the main ideas for achieving stabilisation of the vehicle in front of an object are presented

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The absolute necessity of obtaining 3D information of structured and unknown environments in autonomous navigation reduce considerably the set of sensors that can be used. The necessity to know, at each time, the position of the mobile robot with respect to the scene is indispensable. Furthermore, this information must be obtained in the least computing time. Stereo vision is an attractive and widely used method, but, it is rather limited to make fast 3D surface maps, due to the correspondence problem. The spatial and temporal correspondence among images can be alleviated using a method based on structured light. This relationship can be directly found codifying the projected light; then each imaged region of the projected pattern carries the needed information to solve the correspondence problem. We present the most significant techniques, used in recent years, concerning the coded structured light method