Search results for "FILTER"

Automatic skull stripping in MRI based on morphological filters and fuzzy c-means segmentation

2012

In this paper a new automatic skull stripping method for T1-weighted MR image of human brain is presented. Skull stripping is a process that allows to separate the brain from the rest of tissues. The proposed method is based on a 2D brain extraction making use of fuzzy c-means segmentation and morphological operators applied on transversal slices. The approach is extended to the 3D case, taking into account the result obtained from the preceding slice to solve the organ splitting problem. The proposed approach is compared with BET (Brain Extraction Tool) implemented in MRIcro software.

A Synchronous Reference Frame Robust Predictive Current Control for Three-Phase Grid-Connected Inverters

2010

This paper presents a new predictive current control for three-phase grid-connected inverters in the synchronous reference frame. The control combines a deadbeat control law with a diagonal Luenberger observer to estimate the future value of the grid currents. It provides a decoupled control of the active and reactive power and offers robustness against the computational delay inherent in the digital implementation and against filter and grid-impedance uncertainties. This control exhibits a very fast current response while widely improving the gain and phase margins of the traditional predictive controllers.

Experimental Prototyping of a Microgrid with Mechanical Point of Common Coupling

2020

The smartgrid is a key technology for the sustainable and smart utilization of the renewable energies. In this paper, a prototyping of a microgrid, assembled at the Sustainable Development and Energy Saving Laboratory (SDESLAB) of the University of Palermo, is presented and discussed. In detail, the microgrid presents only one mechanical point of common coupling (PCC) with the main grid and it is electrically separated from the main grid. In this way, the voltage variations of the main grid do not affect the microgrid electric quantities behavior. In order to validate the effectiveness of the voltage and frequency control, several experimental tests and analysis have been carried out. In de…

Tuning of Extended Kalman Filters for Sensorless Motion Control with Induction Motor

2019

This work deals with the tuning of an Extended Kalman Filter for sensorless control of induction motors for electrical traction in automotive. Assuming that the parameters of the induction motor-load model are known, Genetic Algorithms are used for obtaining the system noise covariance matrix, considering the measurement noise covariance matrix equal to the identity matrix. It is shown that only stator currents have to be acquired for reaching this objective, which is easy to accomplish using Hall-effect transducers. In fact, the Genetic Algorithm minimizes, with respect to the system covariance matrix, a suitable measure of the displacement between the stator currents experimentally acquir…

Introduction: Digital Filters and Filter Banks

2015

A basic operation of spectr is filterin. In this introductory chapter, processing of one- and two-dimensional signals by digital filters and filter banks is outlined. A polyphase implementation of multirate filtering is described. The application of filtering with IIR filters, whose transfer functions are rational, is described. Bases and frames in the signals’ space that are generated by perfect reconstruction filter banks are discussed. The Butterworth filters, which are used in further constructions, are introduced.

From Toys to Games: Overcoming the View of Natural Selection as a Filter

2016

Filter Bank: a Directional Approach for Retinal Vessel Segmentation

2017

It is well known that retinal diseases are sometimes identified by tortuosity of the vessels, presence of exudates and hemorrhages while lesions of tissues are associated to diabetic retinopathy, retinopathy of prematurity and more general cerebrovascular problems. One of the main issues in this research field is detecting small curvilinear structures, thus the aim of this contribution is to introduce a non-supervised and automated methodology to detect features such as curvilinear structures in retinal images. The core of the proposed methodology consists in using an approach that resembles the “a trous” wavelet algorithm. With respect to the standard Gabor analysis our methodology is base…

Optimal Filter Estimation for Lucas-Kanade Optical Flow

2012

Optical flow algorithms offer a way to estimate motion from a sequence of images. The computation of optical flow plays a key-role in several computer vision applications, including motion detection and segmentation, frame interpolation, three-dimensional scene reconstruction, robot navigation and video compression. In the case of gradient based optical flow implementation, the pre-filtering step plays a vital role, not only for accurate computation of optical flow, but also for the improvement of performance. Generally, in optical flow computation, filtering is used at the initial level on original input images and afterwards, the images are resized. In this paper, we propose an image filt…

Multiscale Granger causality analysis by à trous wavelet transform

2017

Since interactions in neural systems occur across multiple temporal scales, it is likely that information flow will exhibit a multiscale structure, thus requiring a multiscale generalization of classical temporal precedence causality analysis like Granger's approach. However, the computation of multiscale measures of information dynamics is complicated by theoretical and practical issues such as filtering and undersampling: to overcome these problems, we propose a wavelet-based approach for multiscale Granger causality (GC) analysis, which is characterized by the following properties: (i) only the candidate driver variable is wavelet transformed (ii) the decomposition is performed using the…

A new Adaptive and Progressive Image Transmission Approach using Function Superpositions

2010

International audience; We present a novel approach to adaptive and progressive image transmission, based on the decomposition of an image into compositions and superpositions of monovariate functions. The monovariate functions are iteratively constructed and transmitted, one after the other, to progressively reconstruct the original image: the progressive transmission is performed directly in the 1D space of the monovariate functions and independently of any statistical properties of the image. Each monovariate function contains only a fraction of the pixels of the image. Each new transmitted monovariate function adds data to the previously transmitted monovariate functions. After each tra…