Search results for "pattern"
showing 10 items of 4203 documents
Lossless coding of hyperspectral images with principal polynomial analysis
2014
The transform in image coding aims to remove redundancy among data coefficients so that they can be independently coded, and to capture most of the image information in few coefficients. While the second goal ensures that discarding coefficients will not lead to large errors, the first goal ensures that simple (point-wise) coding schemes can be applied to the retained coefficients with optimal results. Principal Component Analysis (PCA) provides the best independence and data compaction for Gaussian sources. Yet, non-linear generalizations of PCA may provide better performance for more realistic non-Gaussian sources. Principal Polynomial Analysis (PPA) generalizes PCA by removing the non-li…
Optimal Partitions of Strings: A New Class of Burrows-Wheeler Compression Algorithms
2003
The Burrows-Wheeler transform [1] is one of the mainstays of lossless data compression. In most cases, its output is fed to Move to Front or other variations of symbol ranking compression. One of the main open problems [2] is to establish whether Move to Front, or more in general symbol ranking compression, is an essential part of the compression process. We settle this question positively by providing a new class of Burrows-Wheeler algorithms that use optimal partitions of strings, rather than symbol ranking, for the additional step. Our technique is a quite surprising specialization to strings of partitioning techniques devised by Buchsbaum et al. [3] for two-dimensional table compression…
Self-organization of repetitive spike patterns in developing neuronal networks in vitro
2010
The appearance of spontaneous correlated activity is a fundamental feature of developing neuronal networks in vivo and in vitro. To elucidate whether the ontogeny of correlated activity is paralleled by the appearance of specific spike patterns we used a template-matching algorithm to detect repetitive spike patterns in multi-electrode array recordings from cultures of dissociated mouse neocortical neurons between 6 and 15 days in vitro (div). These experiments demonstrated that the number of spiking neurons increased significantly between 6 and 15 div, while a significantly synchronized network activity appeared at 9 div and became the main discharge pattern in the subsequent div. Repetiti…
Automatic segmentation and 3D reconstruction of intravascular ultrasound images for a fast preliminar evaluation of vessel pathologies.
2007
Abstract Intravascular ultrasound (IVUS) imaging is used along with X-ray coronary angiography to detect vessel pathologies. Manual analysis of IVUS images is slow and time-consuming and it is not feasible for clinical purposes. A semi-automated method is proposed to generate 3D reconstructions from IVUS video sequences, so that a fast diagnose can be easily done, quantifying plaque length and severity as well as plaque volume of the vessels under study. The methodology described in this work has four steps: a pre-processing of IVUS images, a segmentation of media–adventitia contour, a detection of intima and plaque and a 3D reconstruction of the vessel. Preprocessing is intended to remove …
Luminous lip-prints as criminal evidence.
2005
Luminescence is specially a useful property for the search of invisible evidences at the scene of a crime. In the latent fingerprints particular case, there are at one's disposal fluorescent reagents for their localization. The study of latent lip prints (that is lip prints from protective lipstick, or permanent or long-lasting lipstick that do not leave any visible marks) is more recent than fingerprints study. Because of the different composition of both types of prints, different reagents have been tried out on their developing. Although, lysochromes are particularly useful reagents to obtain latent lip prints, it may occur on coloured or multicoloured surfaces, the developing is not per…
A smart and operator independent system to delineate tumours in Positron Emission Tomography scans
2018
Abstract Positron Emission Tomography (PET) imaging has an enormous potential to improve radiation therapy treatment planning offering complementary functional information with respect to other anatomical imaging approaches. The aim of this study is to develop an operator independent, reliable, and clinically feasible system for biological tumour volume delineation from PET images. Under this design hypothesis, we combine several known approaches in an original way to deploy a system with a high level of automation. The proposed system automatically identifies the optimal region of interest around the tumour and performs a slice-by-slice marching local active contour segmentation. It automa…
MULTI-SCALE ANALYSIS OF LUNG COMPUTED TOMOGRAPHY IMAGES
2007
A computer-aided detection (CAD) system for the identification of lung internal nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 project. The three modules of our lung CAD system, a segmentation algorithm for lung internal region identification, a multi-scale dot-enhancement filter for nodule candidate selection and a multi-scale neural technique for false positive finding reduction, are described. The results obtained on a dataset of low-dose and thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.
Input-to-state stability for discrete-time nonlinear switched singular systems
2016
Discrete-time nonlinear switched singular systems (SSSs) are investigated.The input-to-state stability (ISS) problems for discrete-time nonlinear SSSs are concerned.The ISS criteria are obtained via average dwell time approach and iterative algorithm of discrete-time systems.The switching rules are optimized and designed. This paper investigates the input-to-state stability (ISS) problems for a class of discrete-time nonlinear switched singular systems (SSSs). Two novel ISS criteria are proposed based on average dwell time (ADT) approach and iterative algorithm of discrete-time systems (IADS). In particular, the following two cases are considered for the underlying systems: the first case i…
Finite-time boundedness for uncertain discrete neural networks with time-delays and Markovian jumps
2014
This paper is concerned with stochastic finite-time boundedness analysis for a class of uncertain discrete-time neural networks with Markovian jump parameters and time-delays. The concepts of stochastic finite-time stability and stochastic finite-time boundedness are first given for neural networks. Then, applying the Lyapunov approach and the linear matrix inequality technique, sufficient criteria on stochastic finite-time boundedness are provided for the class of nominal or uncertain discrete-time neural networks with Markovian jump parameters and time-delays. It is shown that the derived conditions are characterized in terms of the solution to these linear matrix inequalities. Finally, n…
Output-feedback-based H∞ control for vehicle suspension systems with control delay
2014
This paper deals with the problem of output-feedback H∞ control for a class of active quarter-car suspension systems with control delay. The dynamic system of the suspension systems is first formed in terms of the control objectives, i.e., ride comfort, road holding, suspension deflection, and maximum actuator control force. Then, the objective is to the design of the dynamic output-feedback H∞ controller in order to ensure asymptotic stability of the closed-loop system with H∞ disturbance attenuation level and the output constraints. Furthermore, using Lyapunov theory and linear matrix inequality (LMI) approach, the existence of admissible controllers is formulated in terms of LMIs. With t…