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The publishing of the present issue (Volume 13, No 4, 2013) of the journal “Cybernetics and Information Technologies” is financially supported by FP7 project “Advanced Computing for Innovation” (ACOMIN), grant agreement 316087 of Call FP7 REGPOT-2012-2013-1.

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Détails du magazine
Format
Magazine
eISSN
1314-4081
Première publication
13 Mar 2012
Période de publication
4 fois par an
Langues
Anglais

Chercher

Volume 15 (2015): Edition 7 (December 2015)
Special Edition on Information Fusion

Détails du magazine
Format
Magazine
eISSN
1314-4081
Première publication
13 Mar 2012
Période de publication
4 fois par an
Langues
Anglais

Chercher

12 Articles
Accès libre

Preface

Publié en ligne: 19 Jan 2016
Pages: 3 - 4

Résumé

Accès libre

Selected Applications of Scale Spaces in Microscopic Image Analysis

Publié en ligne: 19 Jan 2016
Pages: 5 - 12

Résumé

Abstract

Image segmentation methods can be classified broadly into two classes: intensity-based and geometry-based. Edge detection is the base of many geometry-based segmentation approaches. Scale space theory represents a systematic treatment of the issues of spatially uncorrelated noise with its main application being the detection of edges, using multiple resolution scales, which can be used for subsequent segmentation, classification or encoding. The present paper will give an overview of some recent applications of scale spaces into problems of microscopic image analysis. Particular overviews will be given to Gaussian and alpha-scale spaces. Some applications in the analysis of biomedical images will be presented. The implementation of filters will be demonstrated.

Mots clés

  • Edge-detection
  • Gaussian filtering
  • alpha-stable distributions
Accès libre

Statistical Synthesis of Robust Signal Detection Algorithms under Conditions of Aprioristic Uncertainty

Publié en ligne: 19 Jan 2016
Pages: 13 - 22

Résumé

Abstract

The paper deals with the problem of synthesis of a robust detection algorithm for a harmonic signal on the background of correlated noise and impulse noise. The problem is solved using the empirical Bayes approach and the Tukey model of “pollution”. The efficiency of the algorithm is investigated by the Monte-Carlo method.

Mots clés

  • Signal processing
  • aprioristic uncertainty
  • algorithm
  • robustness
  • radar signal
  • correlated noise
  • pulse interference
Accès libre

2D Video Stabilization for Industrial High-Speed Cameras

Publié en ligne: 19 Jan 2016
Pages: 23 - 34

Résumé

Abstract

The current research concerns the problem of video stabilization “in a point”, which aims to stabilize all video frames according to one chosen reference frame to produce a new video, as by a static camera. Similar task importance relates providing static background in the video sequence that can be usable for correct measurements in the frames when studying dynamic objects in the video. For this aim we propose an efficient combined approach, called “3×3OF9×9”. It fuses our the previous development for fast and rigid 2D video stabilization [2] with the well-known Optical Flow approach, applied by parts via Otsu segmentation, for eliminating the influence of moving objects in the video. The obtained results are compared with those, produced by the commercial software Warp Stabilizer of Adobe-After-Effects CS6.

Mots clés

  • Video stabilization
  • static camera
  • motion vectors
  • optical flow
  • object segmentation
Accès libre

Multichannel Modified Covariance Estimator of a Single-Tone Frequency

Publié en ligne: 19 Jan 2016
Pages: 35 - 44

Résumé

Abstract

The multichannel modified covariance estimator of a single-tone signal frequency is synthesized by using the maximum likelihood method. It is shown that this estimator has an advantage over the estimator averaged by multiple conventional single-channel ones. The particular case of a complex signal is also considered.

Mots clés

  • Single-tone harmonic
  • autoregressive model
  • modified covariance
  • multichannel
  • complex signal
  • frequency
  • estimation
  • maximum likelihood
Accès libre

3D Visualization of Sound Fields Perceived by an Acoustic Camera

Publié en ligne: 19 Jan 2016
Pages: 45 - 57

Résumé

Abstract

The paper summarizes the application results of a recently proposed neuro-fuzzy algorithm for multi-dimensional data clustering to 3-Dimensional (3D) visualization of dynamically perceived sound waves recorded by an acoustic camera. The main focus in the present work is on the developed signal processing algorithm adapted to the specificity of multidimensional data set recorded by the acoustic camera, as well as on the created software package for real-time visualization of the “observed” sound waves propagation.

Mots clés

  • Acoustic camera
  • multi-dimensional data
  • feature extraction
  • direction selective cells (MT neurons)
  • Echo state network
  • fuzzy clustering
Accès libre

Fusion of Images Generated by Radiometric and Active Noise SAR

Publié en ligne: 19 Jan 2016
Pages: 58 - 66

Résumé

Abstract

The work is devoted to fusion of radar and radiometer images. Noise waveform SAR generates radar images of reflective objects of its field of view. A bistatic radiometer with synthetic aperture estimates the thermal radio emissions of the objects along their angular coordinates and even range. The estimated brightness temperatures of rough and smooth surfaces are different, as well as the radar responses from them. Identification of the parameters of objects surfaces may be done using results of joint processing of images generated by both sensors. The optimum and quasi-optimum criteria for fusion of the images were obtained. The latter was experimentally checked. It approves the opportunity to fuse the images for further estimation of some parameters of objects surfaces. The results obtained may be used in environmental and security applications.

Mots clés

  • Image fusion
  • microwave radiometer
  • noise
  • surface roughness
  • detection criteria
  • bistatic radiometer
  • synthetic aperture radar
Accès libre

Multiple Human Biometrics Fusion in Support of Cyberthreats Identification

Publié en ligne: 19 Jan 2016
Pages: 67 - 76

Résumé

Abstract

The paper is outlining an experimentally created framework for multiple human biometrics fusion in support to constantly evolving complex cyberthreats landscape identification. A “scenario method” approach, in combination with experts’ based decision support and users’ biometric “validation-in-advance”, are considered. Practical examples are also given to the proposed ideas, providing a comprehensive outlook to the problem.

Mots clés

  • Biometrics fusion
  • complex cyberthreats identification
  • scenario method
  • decision support
  • validation-in-advance
Accès libre

Two-Dimensional l1-Norm Minimization in SAR Image Reconstriction

Publié en ligne: 19 Jan 2016
Pages: 77 - 87

Résumé

Abstract

A nonconventional image algorithm, based on compressed sensing and l1-norm minimization in Synthetic Aperture Radar (SAR) application is discussed. A discrete model of the earth surface relief and mathematical modeling of SAR signal formation are analytically described. Sparse decomposition in Fourier basis to solve the SAR image reconstruction problem is discussed. In contrast to the classical one-dimensional definition of l1-norm minimization in SAR image reconstruction, applied to an image vector, the present work proposes a two-dimensional definition of l1-norm minimization to the image. To verify the correctness of the algorithm, results of numerical experiments are presented.

Mots clés

  • SAR image reconstruction
  • compressed sensing
  • 2D l-norm minimization
Accès libre

The Impact of the Quality Assessment of Optimal Assignment for Data Association in a Multitarget Tracking Context

Publié en ligne: 19 Jan 2016
Pages: 88 - 98

Résumé

Abstract

The main purpose of this paper is to apply and to test the performance of a new method, based on belief functions, proposed by Dezert et al. in order to evaluate the quality of the individual association pairings provided in the optimal data association solution for improving the performances of multisensor-multitarget tracking systems. The advantages of its implementation in an illustrative realistic surveillance context, when some of the association decisions are unreliable and doubtful and lead to potentially critical mistake, are discussed. A comparison with the results obtained on the base of Generalized Data Association is made.

Mots clés

  • Data association
  • Belief Functions
  • PCR6 fusion rule
  • multitarget tracking
Accès libre

Human Activity Registration Using Multisensor Data Fusion

Publié en ligne: 19 Jan 2016
Pages: 99 - 108

Résumé

Abstract

The paper discusses the feasibility of using smart phone devices for human activity registration and analysis. The functional characteristics of the smart phones and their permanent connectivity allow them to serve as a measurement lab and processing unit. An example of using the smart phones as a sensor data source is described, and the corresponding algorithm and results are given. The possible problems are listed and commented.

Mots clés

  • Smart phone
  • human activity registration
Accès libre

Cloud Based Patient Monitoring Platform Using Android Smartphone Sensors

Publié en ligne: 19 Jan 2016
Pages: 109 - 119

Résumé

Abstract

This paper presents a proof of the concept cloud based patient monitoring and self-care platform, powered by measurements provided from various smartphone sensors. The Cloud platform provides the infrastructure and computational capacity for calculation of the navigation and motion tracking system, fall detection monitoring, as well as emergency notifications. The navigation system uses the pedometer and fusion of the accelerometer, gyroscope and magnetometer sensors. It aims to estimate precisely the patient’s movement and location. While both navigation and tracking systems can independently determine the incremental movement and indoor localization of the patients, they are fused in order to provide more accurate estimations. The fall detection monitoring is enabled by processing the raw data collected from the smartphone’s accelerometer and gyroscope. Furthermore, the cloud system provides various statistics for the physical activity of the patients, based on measurements from the pedometer. Consequently, this paper proposes a proof of the concept cloud based platform that is scalable and highly responsive, used for real-time monitoring and tracking a large number of patients. It also provides indoor navigation and other self-care features.

Mots clés

  • Self-care
  • home care
  • patient monitoring platform
  • android sensor fusion
  • step counter
  • cloud computing
  • indoor navigation
12 Articles
Accès libre

Preface

Publié en ligne: 19 Jan 2016
Pages: 3 - 4

Résumé

Accès libre

Selected Applications of Scale Spaces in Microscopic Image Analysis

Publié en ligne: 19 Jan 2016
Pages: 5 - 12

Résumé

Abstract

Image segmentation methods can be classified broadly into two classes: intensity-based and geometry-based. Edge detection is the base of many geometry-based segmentation approaches. Scale space theory represents a systematic treatment of the issues of spatially uncorrelated noise with its main application being the detection of edges, using multiple resolution scales, which can be used for subsequent segmentation, classification or encoding. The present paper will give an overview of some recent applications of scale spaces into problems of microscopic image analysis. Particular overviews will be given to Gaussian and alpha-scale spaces. Some applications in the analysis of biomedical images will be presented. The implementation of filters will be demonstrated.

Mots clés

  • Edge-detection
  • Gaussian filtering
  • alpha-stable distributions
Accès libre

Statistical Synthesis of Robust Signal Detection Algorithms under Conditions of Aprioristic Uncertainty

Publié en ligne: 19 Jan 2016
Pages: 13 - 22

Résumé

Abstract

The paper deals with the problem of synthesis of a robust detection algorithm for a harmonic signal on the background of correlated noise and impulse noise. The problem is solved using the empirical Bayes approach and the Tukey model of “pollution”. The efficiency of the algorithm is investigated by the Monte-Carlo method.

Mots clés

  • Signal processing
  • aprioristic uncertainty
  • algorithm
  • robustness
  • radar signal
  • correlated noise
  • pulse interference
Accès libre

2D Video Stabilization for Industrial High-Speed Cameras

Publié en ligne: 19 Jan 2016
Pages: 23 - 34

Résumé

Abstract

The current research concerns the problem of video stabilization “in a point”, which aims to stabilize all video frames according to one chosen reference frame to produce a new video, as by a static camera. Similar task importance relates providing static background in the video sequence that can be usable for correct measurements in the frames when studying dynamic objects in the video. For this aim we propose an efficient combined approach, called “3×3OF9×9”. It fuses our the previous development for fast and rigid 2D video stabilization [2] with the well-known Optical Flow approach, applied by parts via Otsu segmentation, for eliminating the influence of moving objects in the video. The obtained results are compared with those, produced by the commercial software Warp Stabilizer of Adobe-After-Effects CS6.

Mots clés

  • Video stabilization
  • static camera
  • motion vectors
  • optical flow
  • object segmentation
Accès libre

Multichannel Modified Covariance Estimator of a Single-Tone Frequency

Publié en ligne: 19 Jan 2016
Pages: 35 - 44

Résumé

Abstract

The multichannel modified covariance estimator of a single-tone signal frequency is synthesized by using the maximum likelihood method. It is shown that this estimator has an advantage over the estimator averaged by multiple conventional single-channel ones. The particular case of a complex signal is also considered.

Mots clés

  • Single-tone harmonic
  • autoregressive model
  • modified covariance
  • multichannel
  • complex signal
  • frequency
  • estimation
  • maximum likelihood
Accès libre

3D Visualization of Sound Fields Perceived by an Acoustic Camera

Publié en ligne: 19 Jan 2016
Pages: 45 - 57

Résumé

Abstract

The paper summarizes the application results of a recently proposed neuro-fuzzy algorithm for multi-dimensional data clustering to 3-Dimensional (3D) visualization of dynamically perceived sound waves recorded by an acoustic camera. The main focus in the present work is on the developed signal processing algorithm adapted to the specificity of multidimensional data set recorded by the acoustic camera, as well as on the created software package for real-time visualization of the “observed” sound waves propagation.

Mots clés

  • Acoustic camera
  • multi-dimensional data
  • feature extraction
  • direction selective cells (MT neurons)
  • Echo state network
  • fuzzy clustering
Accès libre

Fusion of Images Generated by Radiometric and Active Noise SAR

Publié en ligne: 19 Jan 2016
Pages: 58 - 66

Résumé

Abstract

The work is devoted to fusion of radar and radiometer images. Noise waveform SAR generates radar images of reflective objects of its field of view. A bistatic radiometer with synthetic aperture estimates the thermal radio emissions of the objects along their angular coordinates and even range. The estimated brightness temperatures of rough and smooth surfaces are different, as well as the radar responses from them. Identification of the parameters of objects surfaces may be done using results of joint processing of images generated by both sensors. The optimum and quasi-optimum criteria for fusion of the images were obtained. The latter was experimentally checked. It approves the opportunity to fuse the images for further estimation of some parameters of objects surfaces. The results obtained may be used in environmental and security applications.

Mots clés

  • Image fusion
  • microwave radiometer
  • noise
  • surface roughness
  • detection criteria
  • bistatic radiometer
  • synthetic aperture radar
Accès libre

Multiple Human Biometrics Fusion in Support of Cyberthreats Identification

Publié en ligne: 19 Jan 2016
Pages: 67 - 76

Résumé

Abstract

The paper is outlining an experimentally created framework for multiple human biometrics fusion in support to constantly evolving complex cyberthreats landscape identification. A “scenario method” approach, in combination with experts’ based decision support and users’ biometric “validation-in-advance”, are considered. Practical examples are also given to the proposed ideas, providing a comprehensive outlook to the problem.

Mots clés

  • Biometrics fusion
  • complex cyberthreats identification
  • scenario method
  • decision support
  • validation-in-advance
Accès libre

Two-Dimensional l1-Norm Minimization in SAR Image Reconstriction

Publié en ligne: 19 Jan 2016
Pages: 77 - 87

Résumé

Abstract

A nonconventional image algorithm, based on compressed sensing and l1-norm minimization in Synthetic Aperture Radar (SAR) application is discussed. A discrete model of the earth surface relief and mathematical modeling of SAR signal formation are analytically described. Sparse decomposition in Fourier basis to solve the SAR image reconstruction problem is discussed. In contrast to the classical one-dimensional definition of l1-norm minimization in SAR image reconstruction, applied to an image vector, the present work proposes a two-dimensional definition of l1-norm minimization to the image. To verify the correctness of the algorithm, results of numerical experiments are presented.

Mots clés

  • SAR image reconstruction
  • compressed sensing
  • 2D l-norm minimization
Accès libre

The Impact of the Quality Assessment of Optimal Assignment for Data Association in a Multitarget Tracking Context

Publié en ligne: 19 Jan 2016
Pages: 88 - 98

Résumé

Abstract

The main purpose of this paper is to apply and to test the performance of a new method, based on belief functions, proposed by Dezert et al. in order to evaluate the quality of the individual association pairings provided in the optimal data association solution for improving the performances of multisensor-multitarget tracking systems. The advantages of its implementation in an illustrative realistic surveillance context, when some of the association decisions are unreliable and doubtful and lead to potentially critical mistake, are discussed. A comparison with the results obtained on the base of Generalized Data Association is made.

Mots clés

  • Data association
  • Belief Functions
  • PCR6 fusion rule
  • multitarget tracking
Accès libre

Human Activity Registration Using Multisensor Data Fusion

Publié en ligne: 19 Jan 2016
Pages: 99 - 108

Résumé

Abstract

The paper discusses the feasibility of using smart phone devices for human activity registration and analysis. The functional characteristics of the smart phones and their permanent connectivity allow them to serve as a measurement lab and processing unit. An example of using the smart phones as a sensor data source is described, and the corresponding algorithm and results are given. The possible problems are listed and commented.

Mots clés

  • Smart phone
  • human activity registration
Accès libre

Cloud Based Patient Monitoring Platform Using Android Smartphone Sensors

Publié en ligne: 19 Jan 2016
Pages: 109 - 119

Résumé

Abstract

This paper presents a proof of the concept cloud based patient monitoring and self-care platform, powered by measurements provided from various smartphone sensors. The Cloud platform provides the infrastructure and computational capacity for calculation of the navigation and motion tracking system, fall detection monitoring, as well as emergency notifications. The navigation system uses the pedometer and fusion of the accelerometer, gyroscope and magnetometer sensors. It aims to estimate precisely the patient’s movement and location. While both navigation and tracking systems can independently determine the incremental movement and indoor localization of the patients, they are fused in order to provide more accurate estimations. The fall detection monitoring is enabled by processing the raw data collected from the smartphone’s accelerometer and gyroscope. Furthermore, the cloud system provides various statistics for the physical activity of the patients, based on measurements from the pedometer. Consequently, this paper proposes a proof of the concept cloud based platform that is scalable and highly responsive, used for real-time monitoring and tracking a large number of patients. It also provides indoor navigation and other self-care features.

Mots clés

  • Self-care
  • home care
  • patient monitoring platform
  • android sensor fusion
  • step counter
  • cloud computing
  • indoor navigation

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