Search results for " Pattern Recognition"
showing 10 items of 1050 documents
Composite Scaffolds with a Hydrohyapatite Spatial Gradient for Osteochondral Defect Repair
2018
Osteochondral defects derived by traumatic injury or aging related disease are often associated with severe joint pain and progressive loss of joint functions for millions of people worldwide and represent a major challenge for the orthopedic community. Tissue engineering offers new therapeutic approach to repair the osteochondral defects, through the production of scaffolds manufactured to mimic their complex architecture, which consists of cartilage and bone layers. Composite scaffolds based on a PLLA polymeric matrix containing hydroxyapatite (HA) as a filler were prepared through a modified thermally induced phase separation (TIPS) protocol. A suspension was prepared by adding sieved HA…
Nonlinear rotation-invariant pattern recognition by use of the optical morphological correlation.
2000
We introduce a modification of the nonlinear morphological correlation for optical rotation-invariant pattern recognition. The high selectivity of the morphological correlation is conserved compared with standard linear correlation. The operation performs the common morphological correlation by extraction of the information by means of a circular-harmonic component of a reference. In spite of some loss of information good discrimination is obtained, especially for detecting images with a high degree of resemblance. Computer simulations are presented, as well as optical experiments implemented with a joint transform correlator.
Eulerian-Eulerian modelling and computational fluid dynamics simulation of wire mesh demisters in MSF plants
2014
Purpose – The purpose of this study is to focus on simulation of wire mesh demisters in multistage flash desalination (MSF) plants. The simulation is made by the use of computational fluid dynamics (CFD) software. Design/methodology/approach – A steady state and two-dimensional (2D) model was developed to simulate the demister. The model employs an Eulerian-Eulerian approach to simulate the flow of water vapor and brine droplets in the demister. The computational domain included three zones, which are the vapor space above and below the demister and the demister. The demister zone was modeled as a tube bank arrange or as a porous media. Findings – Sensitivity analysis of the model showed t…
Denoising 3D Models with Attributes using Soft Thresholding
2004
International audience; Recent advances in scanning and acquisition technologies allow the construction of complex models from real world scenes. However, the data of those models are generally corrupted by measurement errors. This paper describes an efficient single pass algorithm for denoising irregular meshes of scanned 3D model surfaces. In this algorithm, the frequency content of the model is assessed by a multiresolution analysis that requires only 1-ring neighbourhood without any particular parameterization of the model faces. Denoising is achieved by applying the soft thresholding method to the detail coefficients given by the multiresolution analysis. Our method is suitable for irr…
Détection automatique des repères visuels associés à la dépression
2018
Depression is the most prevalent mood disorder worldwide having a significant impact on well-being and functionality, and important personal, family and societal effects. The early and accurate detection of signs related to depression could have many benefits for both clinicians and affected individuals. The present work aimed at developing and clinically testing a methodology able to detect visual signs of depression and support clinician decisions.Several analysis pipelines were implemented, focusing on motion representation algorithms, including Local Curvelet Binary Patterns-Three Orthogonal Planes (LCBP-TOP), Local Curvelet Binary Patterns- Pairwise Orthogonal Planes (LCBP-POP), Landma…
Real metrology by using depth map information
2004
Usually in an image no real information about the scene’s depth (in terms of absolute distance) is available. In this paper, a method that extracts real depth measures is developed. This approach starts considering a region located in the center of the depth map. This region can be positioned, interactively, in any part of the depth map in order to measure the real distance of every object inside the scene. The histogram local maxima of this region are determined. Among these values the biggest, that represents the gray-level of the most considerable object, is chosen. This gray-level is used in an exponential mapping function that converts, using the input camera settings, the depth map gr…
Multispectral integral imaging acquisition and processing using a monochrome camera and a liquid crystal tunable filter
2012
This paper presents an acquisition system and a procedure to capture 3D scenes in different spectral bands. The acquisition system is formed by a monochrome camera, and a Liquid Crystal Tunable Filter (LCTF) that allows to acquire images at different spectral bands in the [480, 680]nm wavelength interval. The Synthetic Aperture Integral Imaging acquisition technique is used to obtain the elemental images for each wavelength. These elemental images are used to computationally obtain the reconstruction planes of the 3D scene at different depth planes. The 3D profile of the acquired scene is also obtained using a minimization of the variance of the contribution of the elemental images at each …
Gaussian and non-Gaussian stochastic sensitivity analysis of discrete structural systems
2000
Abstract The derivatives of the response of a structural system with respect to the system parameters are termed sensitivities. They play an important role in assessing the effect of uncertainties in the mathematical model of the system and in predicting changes of the response due to changes of the design parameters. In this paper, a time domain approach for evaluating the sensitivity of discrete structural systems to deterministic, as well as to Gaussian or non-Gaussian stochastic input is presented. In particular, in the latter case, the stochastic input has been assumed to be a delta-correlated process and, by using Kronecker algebra extensively, cumulant sensitivities of order higher t…
Self-similar focusing with generalized devil's lenses
2011
[EN] We introduce the generalized devil's lenses (GDLs) as a new family of diffractive kinoform lenses whose structure is based on the generalized Cantor set. The focusing properties of different members of this family are analyzed. It is shown that under plane wave illumination the GDLs give a single main focus surrounded by many subsidiary foci. It is shown that the total number of subsidiary foci is higher than the number of foci corresponding to conventional devil's lenses; however, the self-similar behavior of the axial irradiance is preserved to some extent. (C) 2011 Optical Society of America
Super-resolved imaging with randomly distributed, time- and size-varied particles
2009
In this paper we present a super-resolved approach aimed at overcoming the diffraction limit in imaging systems. It is based on place randomly and time-varied particles having different sizes on the top of the sample. By considering particle sizes smaller than the object's minimum detail that an imaging system can resolve, it is possible to recover a high resolution image from a set of low resolution images while before capturing each image we produce a randomly modified distribution of the particles by vibrating the sample. The simulation process as well as experimental results validates the proposed approach that includes effectively decreasing the F number of the imaging system while bei…