865 resultados para streak camera


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Different interferometric techniques were developed last decade to obtain full field, quantitative, and absolute phase imaging, such as phase-shifting, Fourier phase microscopy, Hilbert phase microscopy or digital holographic microscopy (DHM). Although, these techniques are very similar, DHM combines several advantages. In contrast, to phase shifting, DHM is indeed capable of single-shot hologram recording allowing a real-time absolute phase imaging. On the other hand, unlike to Fourier phase or Hilbert phase microscopy, DHM does not require to record in focus images of the specimen on the digital detector (CCD or CMOS camera), because a numerical focalization adjustment can be performed by a numerical wavefront propagation. Consequently, the depth of view of high NA microscope objectives is numerically extended. For example, two different biological cells, floating at different depths in a liquid, can be focalized numerically from the same digital hologram. Moreover, the numerical propagation associated to digital optics and automatic fitting procedures, permits vibrations insensitive full- field phase imaging and the complete compensation for a priori any image distortion or/and phase aberrations introduced for example by imperfections of holders or perfusion chamber. Examples of real-time full-field phase images of biological cells have been demonstrated. ©2008 COPYRIGHT SPIE

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Diabetes is a common condition affecting around 69,000 people in Northern Ireland. One of the possible complications of diabetes is a condition called diabetic retinopathy, which can cause sight loss and blindness. Retinopathy causes damage to the tiny blood vessels (capillaries) that nourish the retina, the tissues in the back of the eye that deal with light. This can seriously affect vision.Research shows that if retinopathy is identified early, for example through retinal screening, and treated appropriately, blindness can be prevented in the majority of people with diabetes, both type 1 and type 2.Screening programmeIn Northern Ireland, a diabetic retinopathy screening programme (DRSP), run by the Public Health Agency, has been put in place to screen all eligible people with diabetes aged 12 years and over. Dr Bernadette Cullen, Consultant in Public Health Medicine, PHA, said: "Screening detects problems early and allows appropriate treatment to be offered. It is vital that everyone with diabetes attends diabetic retinopathy screening when it is offered. Early detection of potential problems offers a very real opportunity to intervene and, with appropriate treatment, can prevent blindness in the majority of those at risk."The screening testThe screening test involves photographs being taken of the back of each eye, using a special camera. The test is painless and takes about 15 minutes. If the person is over 50 years of age, they will need to have drops put in their eyes about 15 minutes before the test to dilate their pupils.The photographs are sent to the regional screening centre for analysis by trained graders. Results will show whether patients require further referral for assessment or treatment by hospital eye services (HES). If this is not required, screening will be offered again the following year.GPs are informed of all results and if the patient is under the care of a diabetologist, they too will be informed. Patients are informed of results by their GP and if they need an urgent referral, protocols are in place to ensure this happens.Many people with diabetes attend their optometrist (optician) on a regular basis to have a sight test for glasses. It is important they continue to do this - this test is free to people with diabetes. It is also vital that people with diabetes attend for diabetic retinopathy screening when invited, regardless of how or where their diabetes is treated, or whether they visit a hospital consultant/GP for their diabetic care.Patients are invited to screening via their GP practice. An information leaflet to help patients make an informed decision to attend for screening is also sent. This can be accessed via the PHA website: www.publichealth.hscni.net.

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It is a common macroscopic observation that knotted ropes or fishing lines under tension easily break at the knot. However, a more precise localization of the breakage point in knotted macroscopic strings is a difficult task. In the present work, the tightening of knots was numerically simulated, a comparison of strength of different knots was experimentally performed and a high velocity camera was used to precisely localize the site where knotted macroscopic strings break. In the case of knotted spaghetti, the breakage occurs at the position with high curvature at the entry to the knot. This localization results from joint contributions of loading, bending and friction forces into the complex process of knot breakage. The present simulations and experiments are in agreement with recent molecular dynamics simulations of a knotted polymer chain and with experiments performed on actin and DNA filaments. The strength of the knotted string is greatly reduced (down to 50%) by the presence of a knot, therefore reducing the resistance to tension of all materials containing chains of any sort. The present work with macroscopic strings revels some important aspects, which are not accessible by experiments with microscopic chains.

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Until recently, morphotyping, a method evaluating fringe and surface characteristics of streak colonies grown on malt agar, has been recommended as a simple and unexpensive typing method for Candida albicans isolates. The discriminatory power and reproducibility of Hunter's modified scheme of Phongpaichit's morphotyping has been evaluated on 28 C. albicans isolates recovered from the oral cavity of asymptomatic human immunodeficiency virus-positive subjects, and compared to two molecular typing methods: randomly amplified polymorphic DNA (RAPD) fingerprinting, and contour clamped homogeneous electric field (CHEF) electrophoretic karyotyping. Morphological features of streak colonies allowed to distinguish 11 different morphotypes while RAPD fingerprinting yielded 25 different patterns and CHEF electrophoresis recognized 9 karyotypes. The discriminatory power calculated with the formula of Hunter and Gaston was 0.780 for morphotyping, 0.984 for RAPD fingerprinting, and 0.630 for karyotyping. Reproducibility was tested using 43 serial isolates from 15 subjects (2 to 6 isolates per subject) and by repeating the test after one year storage of the isolates. While genetic methods generally recognized a single type for all serial isolates from each of the subjects studied, morphotyping detected strain variations in five subjects in the absence of genetic confirmation. Poor reproducibility was demonstrated repeating morphotyping after one year storage of the isolates since differences in at least one character were detected in 92.9% of the strains.

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The estimation of camera egomotion is a well established problem in computer vision. Many approaches have been proposed based on both the discrete and the differential epipolar constraint. The discrete case is mainly used in self-calibrated stereoscopic systems, whereas the differential case deals with a unique moving camera. The article surveys several methods for mobile robot egomotion estimation covering more than 0.5 million samples using synthetic data. Results from real data are also given

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This paper presents a vision-based localization approach for an underwater robot in a structured environment. The system is based on a coded pattern placed on the bottom of a water tank and an onboard down looking camera. Main features are, absolute and map-based localization, landmark detection and tracking, and real-time computation (12.5 Hz). The proposed system provides three-dimensional position and orientation of the vehicle along with its velocity. Accuracy of the drift-free estimates is very high, allowing them to be used as feedback measures of a velocity-based low-level controller. The paper details the localization algorithm, by showing some graphical results, and the accuracy of the system

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This paper presents an automatic vision-based system for UUV station keeping. The vehicle is equipped with a down-looking camera, which provides images of the sea-floor. The station keeping system is based on a feature-based motion detection algorithm, which exploits standard correlation and explicit textural analysis to solve the correspondence problem. A visual map of the area surveyed by the vehicle is constructed to increase the flexibility of the system, allowing the vehicle to position itself when it has lost the reference image. The testing platform is the URIS underwater vehicle. Experimental results demonstrating the behavior of the system on a real environment are presented

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When underwater vehicles navigate close to the ocean floor, computer vision techniques can be applied to obtain motion estimates. A complete system to create visual mosaics of the seabed is described in this paper. Unfortunately, the accuracy of the constructed mosaic is difficult to evaluate. The use of a laboratory setup to obtain an accurate error measurement is proposed. The system consists on a robot arm carrying a downward looking camera. A pattern formed by a white background and a matrix of black dots uniformly distributed along the surveyed scene is used to find the exact image registration parameters. When the robot executes a trajectory (simulating the motion of a submersible), an image sequence is acquired by the camera. The estimated motion computed from the encoders of the robot is refined by detecting, to subpixel accuracy, the black dots of the image sequence, and computing the 2D projective transform which relates two consecutive images. The pattern is then substituted by a poster of the sea floor and the trajectory is executed again, acquiring the image sequence used to test the accuracy of the mosaicking system

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This paper presents an approach to ameliorate the reliability of the correspondence points relating two consecutive images of a sequence. The images are especially difficult to handle, since they have been acquired by a camera looking at the sea floor while carried by an underwater robot. Underwater images are usually difficult to process due to light absorption, changing image radiance and lack of well-defined features. A new approach based on gray-level region matching and selective texture analysis significantly improves the matching reliability

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This paper presents a complete solution for creating accurate 3D textured models from monocular video sequences. The methods are developed within the framework of sequential structure from motion, where a 3D model of the environment is maintained and updated as new visual information becomes available. The camera position is recovered by directly associating the 3D scene model with local image observations. Compared to standard structure from motion techniques, this approach decreases the error accumulation while increasing the robustness to scene occlusions and feature association failures. The obtained 3D information is used to generate high quality, composite visual maps of the scene (mosaics). The visual maps are used to create texture-mapped, realistic views of the scene

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Omnidirectional cameras offer a much wider field of view than the perspective ones and alleviate the problems due to occlusions. However, both types of cameras suffer from the lack of depth perception. A practical method for obtaining depth in computer vision is to project a known structured light pattern on the scene avoiding the problems and costs involved by stereo vision. This paper is focused on the idea of combining omnidirectional vision and structured light with the aim to provide 3D information about the scene. The resulting sensor is formed by a single catadioptric camera and an omnidirectional light projector. It is also discussed how this sensor can be used in robot navigation applications

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We present a computer vision system that associates omnidirectional vision with structured light with the aim of obtaining depth information for a 360 degrees field of view. The approach proposed in this article combines an omnidirectional camera with a panoramic laser projector. The article shows how the sensor is modelled and its accuracy is proved by means of experimental results. The proposed sensor provides useful information for robot navigation applications, pipe inspection, 3D scene modelling etc

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Catadioptric sensors are combinations of mirrors and lenses made in order to obtain a wide field of view. In this paper we propose a new sensor that has omnidirectional viewing ability and it also provides depth information about the nearby surrounding. The sensor is based on a conventional camera coupled with a laser emitter and two hyperbolic mirrors. Mathematical formulation and precise specifications of the intrinsic and extrinsic parameters of the sensor are discussed. Our approach overcomes limitations of the existing omni-directional sensors and eventually leads to reduced costs of production

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Path planning and control strategies applied to autonomous mobile robots should fulfil safety rules as well as achieve final goals. Trajectory planning applications should be fast and flexible to allow real time implementations as well as environment interactions. The methodology presented uses the on robot information as the meaningful data necessary to plan a narrow passage by using a corridor based on attraction potential fields that approaches the mobile robot to the final desired configuration. It employs local and dense occupancy grid perception to avoid collisions. The key goals of this research project are computational simplicity as well as the possibility of integrating this method with other methods reported by the research community. Another important aspect of this work consist in testing the proposed method by using a mobile robot with a perception system composed of a monocular camera and odometers placed on the two wheels of the differential driven motion system. Hence, visual data are used as a local horizon of perception in which trajectories without collisions are computed by satisfying final goal approaches and safety criteria

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Positioning a robot with respect to objects by using data provided by a camera is a well known technique called visual servoing. In order to perform a task, the object must exhibit visual features which can be extracted from different points of view. Then, visual servoing is object-dependent as it depends on the object appearance. Therefore, performing the positioning task is not possible in presence of non-textured objects or objects for which extracting visual features is too complex or too costly. This paper proposes a solution to tackle this limitation inherent to the current visual servoing techniques. Our proposal is based on the coded structured light approach as a reliable and fast way to solve the correspondence problem. In this case, a coded light pattern is projected providing robust visual features independently of the object appearance