32 research outputs found

    An Image Analysis System for the Assessment of Retinal Microcirculation in Hypertension and Its Clinical Evaluation

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    Abstract — A system for the assessment of hypertension through the measurement of retinal vessels in fundoscopy images, is presented. The proposed approach employs multiple image analysis methods, in an integrated system that is used in clinical practice. Automating the measurement process enables the conduct of a clinical study that, for the first time, shows the correlation between macrovascular and microvascular al-terations, based on numerous measurements acquired by this system. Experience and perspectives gained from clinical usage and evaluation are reported. I

    Modulating the Shape and Size of Backprojection Surfaces to Improve Accuracy in Volumetric Stereo

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    In 3D TV applications, the extraction of 3D representations of dynamic scenes from images plays a central role in the preparation of the presented visual content. This paper focuses on the stereo cue to the extraction of these representations and, in particular, on the recently developed family of volumetric approaches to stereo. Two methods are proposed that improve the accuracy of volumetric stereo approaches, which compare backprojections of image regions to establish stereo correspondences. The proposed methods are based on maximizing the utilization of the available image resolution, as well as, equalizing the sampled image area across pairs of image regions that are compared

    Comparison of Appearance-Based and Geometry-Based Bubble Detectors

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    3D visual sensing of human hand for remote operation of a robotic hand

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    New low cost sensors and open free libraries for 3D image processing are making important advances in robot vision applications possible, such as three-dimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a novel method for recognizing and tracking the fingers of a human hand is presented. This method is based on point clouds from range images captured by a RGBD sensor. It works in real time and it does not require visual marks, camera calibration or previous knowledge of the environment. Moreover, it works successfully even when multiple objects appear in the scene or when the ambient light is changed. Furthermore, this method was designed to develop a human interface to control domestic or industrial devices, remotely. In this paper, the method was tested by operating a robotic hand. Firstly, the human hand was recognized and the fingers were detected. Secondly, the movement of the fingers was analysed and mapped to be imitated by a robotic hand.The research leading to these results received funding from the Spanish Government and European FEDER funds (DPI2012-32390) and the Valencia Regional Government (GV2012/102 and PROMETEO/2013/085)
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