Examinando por Materia "image processing"
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Ítem Analysis of periodic structures with Fourier description and neuronal network(IMPRENTA UNIV ANTIOQUIA, 2007-06-01) DIAZ, ADALBERTO GABRIEL; Gabriel Diaz, Adalberto; Universidad EAFIT. Departamento de Ingeniería de Producción; Ingeniería, Energía, Exergía y Sostenibilidad (IEXS)This work is developed in a project of textile lattices inspection. The structure of a superficial texture is manifested with a behavior on the base of a model known as pattern which, is associated with a group of characteristics that define it as such. The identification process and classification of shortcomings in the texture consists on establishing a region of conformity in the coordinated space defined by the pattern's characteristics. The reduction process of this m-dimensional space, helps to its identification in an n-dimensional space, such that m > n, where the classification system actually depends on the characteristics of the new space, where the new characteristics truly contain the classification information. The space characteristics allow for the identification of the pattern as such in the place that is explored. The characteristic frequency corresponds to a reduction of the classification space, making it more generic in the area over the image. The classification system is modeled with neuronal networks algorithms and the complexity of the surfaces of decision is solved starting from the architecture and the algorithms of training of the neuronal net.Ítem Efficient use of mobile devices for quantification of pressure injury images(IOS Press, 2018-01-01) Garcia-Zapirain B; Sierra-Sosa D; Ortiz P D; Isaza-Monsalve M; Elmaghraby A; Garcia-Zapirain B; Sierra-Sosa D; Ortiz P D; Isaza-Monsalve M; Elmaghraby A; Universidad EAFIT. Departamento de Ciencias; Modelado MatemáticoPressure Injuries are chronic wounds that are formed due to the constriction of the soft tissues against bone prominences. In order to assess these injuries, the medical personnel carry out the evaluation and diagnosis using visual methods and manual measurements, which can be inaccurate and may generate discomfort in the patients. By using segmentation techniques, the Pressure Injuries can be extracted from an image and accurately parameterized, leading to a correct diagnosis. In general, these techniques are based on the solution of differential equations and the involved numerical methods are demanding in terms of computational resources. In previous work, we proposed a technique developed using toroidal parametric equations for image decomposition and segmentation without solving differential equations. In this paper, we present the development of a mobile application useful for the non-contact assessment of Pressure Injuries based on the toroidal decomposition from images. The usage of this technique allows us to achieve an accurate segmentation almost 8 times faster than Active Contours without Edges (ACWE) and Dynamic Contours methods.We describe the techniques and the implementation for Android devices using Python and Kivy. This application allows for the segmentation and parameterization of injuries, obtain relevant information for the diagnosis and tracking the evolution of patient's injuries. © 2018 - IOS Press and the authors.Ítem Shack-Hartmann centroid detection using the spiral phase transform(OSA - The Optical Society of America, 2012-01-01) Vargas, J.; Restrepo, R.; Estrada, J.C.; Sorzano, C.O.S.; Du, Y.-Z.; Carazo, J.M.; Universidad EAFIT. Departamento de Ciencias Básicas; Óptica AplicadaWe present a Shack-Hartmann (SH) centroid detection algorithm capable to measure in presence of strong noise, background illumination and spot modulating signals, which are typical limiting factors of traditional centroid detection algorithms. The proposed method is based on performing a normalization of the SH pattern using the spiral phase transform method and Fourier filtering. The spot centroids are then obtained using global thresholding and weighted average methods. We have tested the algorithm with simulations and experimental data obtaining satisfactory results. A complete MATLAB package that can reproduce all the results can be downloaded from [http://goo.gl/o2JhD]. © 2012 Optical Society of America.Ítem Volume Visual Attention Maps (VVAM) in ray-casting rendering(IOS Press, 2012-01-01) Beristain, A.; Congote, J.; Ruiz, O.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEThis paper presents an extension visual attention maps for volume data visualization, where eye fixation points become rays in the 3D space, and the visual attention map becomes a volume. This Volume Visual Attention Map (VVAM) is used to interactively enhance a ray-casting based direct volume rendering (DVR) visualization. The practical application of this idea into the biomedical image visualization field is explored for interactive visualization. © 2012 The authors and IOS Press. All rights reserved.Ítem Volumetric non-local-means based speckle reduction for optical coherence tomography(OSA - The Optical Society, 2018-07-01) Cuartas-Vélez, C.; Restrepo, R.; Bouma, B.E.; Uribe-Patarroyo, N.; Universidad EAFIT. Departamento de Ciencias Básicas; Óptica AplicadaWe present a novel tomographic non-local-means based despeckling technique, TNode, for optical coherence tomography. TNode is built upon a weighting similarity criterion derived for speckle in a three-dimensional similarity window. We present an implementation using a two-dimensional search window, enabling the despeckling of volumes in the presence of motion artifacts, and an implementation using a three-dimensional window with improved performance in motion-free volumes. We show that our technique provides effective speckle reduction, comparable with B-scan compounding or out-of-plane averaging, while preserving isotropic resolution, even to the level of speckle-sized structures. We demonstrate its superior despeckling performance in a phantom data set, and in an ophthalmic data set we show that small, speckle-sized retinal vessels are clearly preserved in intensity images en-face and in two orthogonal, cross-sectional views. TNode does not rely on dictionaries or segmentation and therefore can readily be applied to arbitrary optical coherence tomography volumes. We show that despeckled esophageal volumes exhibit improved image quality and detail, even in the presence of significant motion artifacts. © 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement.