1000 resultados para Imatges mèdiques -- Processament


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This work proposes the detection of red peaches in orchard images based on the definition of different linear color models in the RGB vector color space. The classification and segmentation of the pixels of the image is then performed by comparing the color distance from each pixel to the different previously defined linear color models. The methodology proposed has been tested with images obtained in a real orchard under natural light. The peach variety in the orchard was the paraguayo (Prunus persica var. platycarpa) peach with red skin. The segmentation results showed that the area of the red peaches in the images was detected with an average error of 11.6%; 19.7% in the case of bright illumination; 8.2% in the case of low illumination; 8.6% for occlusion up to 33%; 12.2% in the case of occlusion between 34 and 66%; and 23% for occlusion above 66%. Finally, a methodology was proposed to estimate the diameter of the fruits based on an ellipsoidal fitting. A first diameter was obtained by using all the contour pixels and a second diameter was obtained by rejecting some pixels of the contour. This approach enables a rough estimate of the fruit occlusion percentage range by comparing the two diameter estimates.

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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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A method for optimizing the strength of a parametric phase mask for a wavefront coding imaging system is presented. The method is based on an optimization process that minimizes a proposed merit function. The goal is to achieve modulation transfer function invariance while quantitatively maintaining nal image delity. A parametric lter that copes with the noise present in the captured images is used to obtain the nal images, and this lter is optimized. The whole process results in optimum phase mask strength and optimal parameters for the restoration lter. The results for a particular optical system are presented and tested experimentally in the labo- ratory. The experimental results show good agreement with the simulations, indicating that the procedure is useful.

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La investigació actual necessita recórrer en nombroses ocasions a la imatge, i encara ho podria fer més. El registre d'imatges s'ha convertit avui en una feina senzilla i económica, almenys en relació amb la situació de fa vint anys. I des de fa amb prou feines un parell d'anys, el tractament de la imatge animada mitjançant tècniques digitals encara s'ha simplificat més, alhora que ha proporcionat nous canvis que permeten explorar la realitat.

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The Cherenkov light flashes produced by Extensive Air Showers are very short in time. A high bandwidth and fast digitizing readout, therefore, can minimize the influence of the background from the light of the night sky, and improve the performance in Cherenkov telescopes. The time structure of the Cherenkov image can further be used in single-dish Cherenkov telescopes as an additional parameter to reduce the background from unwanted hadronic showers. A description of an analysis method which makes use of the time information and the subsequent improvement on the performance of the MAGIC telescope (especially after the upgrade with an ultra fast 2 GSamples/s digitization system in February 2007) will be presented. The use of timing information in the analysis of the new MAGIC data reduces the background by a factor two, which in turn results in an enhancement of about a factor 1.4 of the flux sensitivity to point-like sources, as tested on observations of the Crab Nebula.

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The CORNISH project is the highest resolution radio continuum survey of the Galactic plane to date. It is the 5 GHz radio continuum part of a series of multi-wavelength surveys that focus on the northern GLIMPSE region (10° < l < 65°), observed by the Spitzer satellite in the mid-infrared. Observations with the Very Large Array in B and BnA configurations have yielded a 1.''5 resolution Stokes I map with a root mean square noise level better than 0.4 mJy beam 1. Here we describe the data-processing methods and data characteristics, and present a new, uniform catalog of compact radio emission. This includes an implementation of automatic deconvolution that provides much more reliable imaging than standard CLEANing. A rigorous investigation of the noise characteristics and reliability of source detection has been carried out. We show that the survey is optimized to detect emission on size scales up to 14'' and for unresolved sources the catalog is more than 90% complete at a flux density of 3.9 mJy. We have detected 3062 sources above a 7σ detection limit and present their ensemble properties. The catalog is highly reliable away from regions containing poorly sampled extended emission, which comprise less than 2% of the survey area. Imaging problems have been mitigated by down-weighting the shortest spacings and potential artifacts flagged via a rigorous manual inspection with reference to the Spitzer infrared data. We present images of the most common source types found: H II regions, planetary nebulae, and radio galaxies. The CORNISH data and catalog are available online at http://cornish.leeds.ac.uk.

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Aquest informe tècnic mostra la classificació, incidència, característiques i diagnòstic dels tumors ossis primaris i secundaris metastàsics més freqüents a partir de 145 radiografies digitalitzades

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Aquest projecte s’emmarca dins de l’àmbit de la visió per computador, concretament en la utilització de dades de profunditat obtingudes a través d’un emissor i sensor de llum infraroja.El propòsit principal d’aquest projecte és mostrar com adaptar aquestes tecnologies, a l’abast de qualsevol particular, de forma que un usuari durant la pràctica d’una activitat esportiva concreta, rebi informació visual continua dels moviments i gestos incorrectes que està realitzant, en base a uns paràmetres prèviament establerts.L’objectiu d’aquest projecte consisteix en fer una lectura constant en temps real d’una persona practicant una selecció de diverses activitats esportives estàtiques utilitzant un sensor Kinect. A través de les dades obtingudes pel sensor Kinect i utilitzant les llibreries de “skeleton traking” proporcionades per Microsoft s’haurà d’interpretar les dades posturals obtingudes per cada tipus d’esport i indicar visualment i d’una manera intuïtiva els errors que està cometent en temps real, de manera que es vegi clarament a quina part del seu cos realitza un moviment incorrecte per tal de poder corregir-lo ràpidament. El entorn de desenvolupament que s’utilitza per desenvolupar aquesta aplicació es Microsoft Viusal Studio 2010.El llenguatge amb el qual es treballarà sobre Microsoft Visual Studio 2010 és C#

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El present treball de recerca posa de relleu que la música és un element fonamental de la configuració de les societats humanes actuals i analitza un cas concret, el de l'artista britànic David Bowie, per il·lustrar els mecanismes pels quals un artista pot convertir-se en una icona i, d'aquesta manera, influir decissivament en la configuració d'elements de l'imaginari social compartit.

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Phase encoded nano structures such as Quick Response (QR) codes made of metallic nanoparticles are suggested to be used in security and authentication applications. We present a polarimetric optical method able to authenticate random phase encoded QR codes. The system is illuminated using polarized light and the QR code is encoded using a phase-only random mask. Using classification algorithms it is possible to validate the QR code from the examination of the polarimetric signature of the speckle pattern. We used Kolmogorov-Smirnov statistical test and Support Vector Machine algorithms to authenticate the phase encoded QR codes using polarimetric signatures.

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Changes in the angle of illumination incident upon a 3D surface texture can significantly alter its appearance, implying variations in the image texture. These texture variations produce displacements of class members in the feature space, increasing the failure rates of texture classifiers. To avoid this problem, a model-based texture recognition system which classifies textures seen from different distances and under different illumination directions is presented in this paper. The system works on the basis of a surface model obtained by means of 4-source colour photometric stereo, used to generate 2D image textures under different illumination directions. The recognition system combines coocurrence matrices for feature extraction with a Nearest Neighbour classifier. Moreover, the recognition allows one to guess the approximate direction of the illumination used to capture the test image

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In this paper a colour texture segmentation method, which unifies region and boundary information, is proposed. The algorithm uses a coarse detection of the perceptual (colour and texture) edges of the image to adequately place and initialise a set of active regions. Colour texture of regions is modelled by the conjunction of non-parametric techniques of kernel density estimation (which allow to estimate the colour behaviour) and classical co-occurrence matrix based texture features. Therefore, region information is defined and accurate boundary information can be extracted to guide the segmentation process. Regions concurrently compete for the image pixels in order to segment the whole image taking both information sources into account. Furthermore, experimental results are shown which prove the performance of the proposed method

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An unsupervised approach to image segmentation which fuses region and boundary information is presented. The proposed approach takes advantage of the combined use of 3 different strategies: the guidance of seed placement, the control of decision criterion, and the boundary refinement. The new algorithm uses the boundary information to initialize a set of active regions which compete for the pixels in order to segment the whole image. The method is implemented on a multiresolution representation which ensures noise robustness as well as computation efficiency. The accuracy of the segmentation results has been proven through an objective comparative evaluation of the method

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This paper presents a novel technique to align partial 3D reconstructions of the seabed acquired by a stereo camera mounted on an autonomous underwater vehicle. Vehicle localization and seabed mapping is performed simultaneously by means of an Extended Kalman Filter. Passive landmarks are detected on the images and characterized considering 2D and 3D features. Landmarks are re-observed while the robot is navigating and data association becomes easier but robust. Once the survey is completed, vehicle trajectory is smoothed by a Rauch-Tung-Striebel filter obtaining an even better alignment of the 3D views and yet a large-scale acquisition of the seabed