Search results for "ILTER"
showing 10 items of 1040 documents
Optical design improvement for noncontact skin cancer diagnostic device
2018
Multispectral diffuse reflectance imaging and autofluorescence photo-bleaching imaging are methods that have been investigated for use in skin disorder diagnostics. In response to the ever-increasing incidence of skin cancer in light skinned populations a new device has been designed incorporating both of these methods. The aim of the study was to create a device that is most efficient in terms of hardware and software parameters for the screening of malignant and benign skin lesions. A set of 525 nm, 630 nm and 980 nm LEDs were used to illuminate the skin area at three wavelengths [1] and a set of 405 nm LEDs were used to induce the skin autofluorescence [2]. For a more homogenous illumina…
The Kalman Filter and Its Applications in GNSS and INS
2011
This chapter contains sections titled: Introduction Review of Kalman Filtering and Extended Kalman Filtering for Navigation EKF-Based PVT Computation in a Stand-Alone GNSS Receiver Inertial Navigation Fundamentals IMU Alignment General Architecture for the Loose Integration General Architecture for the Tight Integration General Architecture for the Ultra-Tight Integration Conclusions References Appendix A
FastSLAM 2.0: Least-Squares Approach
2006
In this paper, we present a set of robust and efficient algorithms with O(N) cost for the following situations: object detection with a laser ranger; mobile robot pose estimation and a FastSLAM improved implementation. Objected detection is mainly based on a novel multiple line fitting method, related with walls at the environment. This method assumes that walls at the environment constitute a regular constrained angles. A line-based pose estimation method is also proposed, based on Least-Squares (LS). This method performs the matching of detected lines and estimated map lines and it can provide the global pose estimation under assumption of known Data-Association. FastSLAM 1.0 has been imp…
AUTOMATIC TAKE-OFF OR LANDING PATH FOLLOWING IN TURBULENT AIR FOR UAS - AN EKF BASED PROCEDURE
2015
By using the Extended Kalman Filter (EKF) an accurate take-off or landing flight path following in turbulent air is performed. The tuned up procedure employs simultaneously two different EKF: the first one estimates gust disturbances, the second one affords to determine the necessary controls displacements for rejecting those ones. In particular, the first filter, by using instrumental measurements gathered in turbulent air, estimates wind components. The second one obtains command laws able to follow the desired flight path. To perform this task aerodynamic coefficients have been modified by adding entirely new derivatives or synthetic increments to basic ones whose might the kind of chang…
SIFT Matching by Context Exposed
2023
This paper investigates how to step up local image descriptor matching by exploiting matching context information. Two main contexts are identified, originated respectively from the descriptor space and from the keypoint space. The former is generally used to design the actual matching strategy while the latter to filter matches according to the local spatial consistency. On this basis, a new matching strategy and a novel local spatial filter, named respectively blob matching and Delaunay Triangulation Matching (DTM) are devised. Blob matching provides a general matching framework by merging together several strategies, including rank-based pre-filtering as well as many-to-many and symmetri…
A blind Robust Image Watermarking Approach exploiting the DFT Magnitude
2019
Due to the current progress in Internet, digital contents (video, audio and images) are widely used. Distribution of multimedia contents is now faster and it allows for easy unauthorized reproduction of information. Digital watermarking came up while trying to solve this problem. Its main idea is to embed a watermark into a host digital content without affecting its quality. Moreover, watermarking can be used in several applications such as authentication, copy control, indexation, Copyright protection, etc. In this paper, we propose a blind robust image watermarking approach as a solution to the problem of copyright protection of digital images. The underlying concept of our method is to a…
Group Importance Sampling for particle filtering and MCMC
2018
Bayesian methods and their implementations by means of sophisticated Monte Carlo techniques have become very popular in signal processing over the last years. Importance Sampling (IS) is a well-known Monte Carlo technique that approximates integrals involving a posterior distribution by means of weighted samples. In this work, we study the assignation of a single weighted sample which compresses the information contained in a population of weighted samples. Part of the theory that we present as Group Importance Sampling (GIS) has been employed implicitly in different works in the literature. The provided analysis yields several theoretical and practical consequences. For instance, we discus…
Compressed Particle Methods for Expensive Models With Application in Astronomy and Remote Sensing
2021
In many inference problems, the evaluation of complex and costly models is often required. In this context, Bayesian methods have become very popular in several fields over the last years, in order to obtain parameter inversion, model selection or uncertainty quantification. Bayesian inference requires the approximation of complicated integrals involving (often costly) posterior distributions. Generally, this approximation is obtained by means of Monte Carlo (MC) methods. In order to reduce the computational cost of the corresponding technique, surrogate models (also called emulators) are often employed. Another alternative approach is the so-called Approximate Bayesian Computation (ABC) sc…
Futures pricing in electricity markets based on stable CARMA spot models
2012
We present a new model for the electricity spot price dynamics, which is able to capture seasonality, low-frequency dynamics and the extreme spikes in the market. Instead of the usual purely deterministic trend we introduce a non-stationary independent increments process for the low-frequency dynamics, and model the large uctuations by a non-Gaussian stable CARMA process. The model allows for analytic futures prices, and we apply these to model and estimate the whole market consistently. Besides standard parameter estimation, an estimation procedure is suggested, where we t the non-stationary trend using futures data with long time until delivery, and a robust L 1 -lter to nd the states of …
On resampling schemes for particle filters with weakly informative observations
2022
We consider particle filters with weakly informative observations (or `potentials') relative to the latent state dynamics. The particular focus of this work is on particle filters to approximate time-discretisations of continuous-time Feynman--Kac path integral models -- a scenario that naturally arises when addressing filtering and smoothing problems in continuous time -- but our findings are indicative about weakly informative settings beyond this context too. We study the performance of different resampling schemes, such as systematic resampling, SSP (Srinivasan sampling process) and stratified resampling, as the time-discretisation becomes finer and also identify their continuous-time l…