Rivista e Edizione

Volume 22 (2022): Edizione 3 (September 2022)

Volume 22 (2022): Edizione 2 (June 2022)

Volume 22 (2022): Edizione 1 (March 2022)

Volume 21 (2021): Edizione 4 (December 2021)

Volume 21 (2021): Edizione 3 (September 2021)

Volume 21 (2021): Edizione 2 (June 2021)

Volume 21 (2021): Edizione 1 (March 2021)

Volume 20 (2020): Edizione 6 (December 2020)
Special Edizione on New Developments in Scalable Computing

Volume 20 (2020): Edizione 5 (December 2020)
Special issue on Innovations in Intelligent Systems and Applications

Volume 20 (2020): Edizione 4 (November 2020)

Volume 20 (2020): Edizione 3 (September 2020)

Volume 20 (2020): Edizione 2 (June 2020)

Volume 20 (2020): Edizione 1 (March 2020)

Volume 19 (2019): Edizione 4 (November 2019)

Volume 19 (2019): Edizione 3 (September 2019)

Volume 19 (2019): Edizione 2 (June 2019)

Volume 19 (2019): Edizione 1 (March 2019)

Volume 18 (2018): Edizione 5 (May 2018)
Special Thematic Edizione on Optimal Codes and Related Topics

Volume 18 (2018): Edizione 4 (November 2018)

Volume 18 (2018): Edizione 3 (September 2018)

Volume 18 (2018): Edizione 2 (June 2018)

Volume 18 (2018): Edizione 1 (March 2018)

Volume 17 (2017): Edizione 5 (December 2017)
Special Edizione With Selected Papers From The Workshop “Two Years Avitohol: Advanced High Performance Computing Applications 2017

Volume 17 (2017): Edizione 4 (November 2017)

Volume 17 (2017): Edizione 3 (September 2017)

Volume 17 (2017): Edizione 2 (June 2017)

Volume 17 (2017): Edizione 1 (March 2017)

Volume 16 (2016): Edizione 6 (December 2016)
Special issue with selection of extended papers from 6th International Conference on Logistic, Informatics and Service Science LISS’2016

Volume 16 (2016): Edizione 5 (October 2016)
Edizione Title: Special Edizione on Application of Advanced Computing and Simulation in Information Systems

Volume 16 (2016): Edizione 4 (December 2016)

Volume 16 (2016): Edizione 3 (September 2016)

Volume 16 (2016): Edizione 2 (June 2016)

Volume 16 (2016): Edizione 1 (March 2016)

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

Volume 15 (2015): Edizione 6 (December 2015)
Special Edizione on Logistics, Informatics and Service Science

Volume 15 (2015): Edizione 5 (April 2015)
Special Edizione on Control in Transportation Systems

Volume 15 (2015): Edizione 4 (November 2015)

Volume 15 (2015): Edizione 3 (September 2015)

Volume 15 (2015): Edizione 2 (June 2015)

Volume 15 (2015): Edizione 1 (March 2015)

Volume 14 (2014): Edizione 5 (December 2014)
Special Edizione

Volume 14 (2014): Edizione 4 (December 2014)

Volume 14 (2014): Edizione 3 (September 2014)

Volume 14 (2014): Edizione 2 (June 2014)

Volume 14 (2014): Edizione 1 (March 2014)

Volume 13 (2013): Edizione Special-Edizione (December 2013)

Volume 13 (2013): Edizione 4 (December 2013)
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.

Volume 13 (2013): Edizione 3 (September 2013)

Volume 13 (2013): Edizione 2 (June 2013)

Volume 13 (2013): Edizione 1 (March 2013)

Volume 12 (2012): Edizione 4 (December 2012)

Volume 12 (2012): Edizione 3 (September 2012)

Volume 12 (2012): Edizione 2 (June 2012)

Volume 12 (2012): Edizione 1 (March 2012)

Dettagli della rivista
Formato
Rivista
eISSN
1314-4081
Pubblicato per la prima volta
13 Mar 2012
Periodo di pubblicazione
4 volte all'anno
Lingue
Inglese

Cerca

Volume 15 (2015): Edizione 1 (March 2015)

Dettagli della rivista
Formato
Rivista
eISSN
1314-4081
Pubblicato per la prima volta
13 Mar 2012
Periodo di pubblicazione
4 volte all'anno
Lingue
Inglese

Cerca

11 Articoli
Accesso libero

α-Nearness Ant Colony System with Adaptive Strategies and Performance Analysis

Pubblicato online: 13 Mar 2015
Pagine: 3 - 13

Astratto

Abstract

This paper proposes an improved ant colony system with adaptive strategies, called α

-AACS and considers its performance. First of all, we introduce α-nearness based on the minimum 1-tree for the disadvantage of the Ant Colony System (ACS), which better reflects the chances of a given link, being a member of an optimal tour. Next, we utilize the adaptive operator to balance the population diversity and the convergence speed and propose other optimizations for ACS. Finally, we present an account of the experiments and the statistic-based analysis, which clearly shows that α-AACS has a better global searching ability in finding the best solutions and better performance in solution variation.

Keywords

  • Ant colony system
  • α-nearness
  • minimum 1-tree
  • lower bound
  • adaptive strategy
Accesso libero

A Component Retrieval Tree Matching Algorithm Based on a Faceted Classification Scheme

Pubblicato online: 13 Mar 2015
Pagine: 14 - 23

Astratto

Abstract

An efficient scheme of component retrieval can significantly reduce the cost of software reuse. For this purpose, a method of successfully retrieving of specified components from the component repository is a crucial consideration. However, neither the retrieval efficiency, nor the query-matching rate of the traditional method, which is based on a faceted classification scheme, satisfies the requirements of component retrieval. In this paper a novel component retrieval method combining the features of the faceted classification scheme and the theory of tree matching is proposed. This method not only accurately retrieves components that match queries, but also considers any incomplete descriptions of the retrieval component to completely ensure the relaxation ability of the component retrieval. The experimental results show that the retrieval matching method proposed is highly efficient, and it retrieves feasibly and efficiently the components.

Keywords

  • Component repository
  • component retrieval
  • faceted classification scheme
  • software reuse
  • tree matching
Accesso libero

A Distributed Adaptive Neuro-Fuzzy Network for Chaotic Time Series Prediction

Pubblicato online: 13 Mar 2015
Pagine: 24 - 33

Astratto

Abstract

In this paper a Distributed Adaptive Neuro-Fuzzy Architecture (DANFA) model with a second order Takagi-Sugeno inference mechanism is presented. The proposed approach is based on the simple idea to reduce the number of the fuzzy rules and the computational load, when modeling nonlinear systems. As a learning procedure for the designed structure a two-step gradient descent algorithm with a fixed learning rate is used. To demonstrate the potentials of the selected approach, simulation experiments with two benchmark chaotic time systems − Mackey-Glass and Rossler are studied. The results obtained show an accurate model performance with a minimal prediction error.

Keywords

  • Distributed fuzzy neural network
  • fuzzy-neural models
  • nonlinear identification
  • Takagi-Sugeno fuzzy inference
  • NARX
Accesso libero

Adaptive Fuzzy H Robust Tracking Control for Nonlinear MIMO Systems

Pubblicato online: 13 Mar 2015
Pagine: 34 - 45

Astratto

Abstract

In this paper an adaptive fuzzy H∞ robust tracking control scheme is developed for a class of uncertain nonlinear Multi-Input and Multi-Output (MIMO) systems. Firstly, fuzzy logic systems are introduced to approximate the unknown nonlinear function of the system by an adaptive algorithm. Next, a H∞ robust compensator controller is employed to eliminate the effect of the approximation error and external disturbances. Consequently, a fuzzy adaptive robust controller is proposed, such that the tracking error of the resulting closed-loop system converges to zero and the tracking robustness performance can be guaranteed. The simulation results performed on a two-link robotic manipulator demonstrate the validity of the proposed control scheme.

Keywords

  • Nonlinear MIMO system
  • adaptive fuzzy control
  • H∞ control
Accesso libero

Privacy Preservation of a Group and Secure Data Storage in Cloud Environment

Pubblicato online: 13 Mar 2015
Pagine: 46 - 54

Astratto

Abstract

Cloud computing has become a victorious archetype for data storage, as well as for computation purposes. Greater than ever it concerns user’s privacy, so that data security in a cloud is increasing day by day. Ensuring security and privacy for data organization and query dispensation in the cloud is important for superior and extended uses of cloud based technologies. Cloud users can barely have the full benefits of cloud computing if we can ensure the real user’s privacy and his data security concerns this approach along with storing thin-skinned personal information in databases and software spread around the cloud. There are numerous service suppliers in WWW (World Wide Web), who can supply each service as a cloud. These cloud services will switch over data with a supplementary cloud, so that when the data is exchanged between the clouds, the problem of confidentiality revelation exists. So the privacy revelation problem concerning a person or a corporation is unavoidably open when releasing or data distributing in the cloud service. Confidentiality is a significant issue in any cloud computing environment. In this paper we propose and implement a mechanism to maintain privacy and secure data storage for group members or a community in cloud environment.

Parole chiave

  • Cloud computing
  • privacy
  • data security
  • community
  • GDH
Accesso libero

Public Opinion Evolution Based on Complex Networks

Pubblicato online: 13 Mar 2015
Pagine: 55 - 68

Astratto

Abstract

The Sznajd model of sociophysics can describe the mechanism of making a decision in a closed community. The Complex Agent Networks (CAN) model is studied, based on the adaptability, autonomy and activity of the individuals, as well as the complex interactions of individuals in an open community for probing into evolution of the public opinion. With the help of the theory of complex adaptive systems and the methods of complex networks, the structure of agents, the dynamic networks scenarios and the evolutionary process of the agents are described. The simulation results of CAN model show that all individuals cannot reach a final consensus through mutual consultations when the small world networks rewiring probability p is less than a specified threshold. But when the rewiring probability p is larger than the given threshold, all individuals will eventually come to a finial consensus, and that the rewiring probability p increases, whereas the time of emergence of the public opinion will be significantly reduced. It is quite obvious that in real community the mass media and many other mechanisms have an effect on the evolutionary process of the public opinion.

Keywords

  • Complex networks
  • public opinion
  • complex adaptive systems
  • small world networks
Accesso libero

QoS Guaranteed Intelligent Routing Using Hybrid PSO-GA in Wireless Mesh Networks

Pubblicato online: 13 Mar 2015
Pagine: 69 - 83

Astratto

Abstract

In Multi-Channel Multi-Radio Wireless Mesh Networks (MCMR-WMN), finding the optimal routing by satisfying the Quality of Service (QoS) constraints is an ambitious task. Multiple paths are available from the source node to the gateway for reliability, and sometimes it is necessary to deal with failures of the link in WMN. A major challenge in a MCMR-WMN is finding the routing with QoS satisfied and an interference free path from the redundant paths, in order to transmit the packets through this path. The Particle Swarm Optimization (PSO) is an optimization technique to find the candidate solution in the search space optimally, and it applies artificial intelligence to solve the routing problem. On the other hand, the Genetic Algorithm (GA) is a population based meta-heuristic optimization algorithm inspired by the natural evolution, such as selection, mutation and crossover. PSO can easily fall into a local optimal solution, at the same time GA is not suitable for dynamic data due to the underlying dynamic network. In this paper we propose an optimal intelligent routing, using a Hybrid PSO-GA, which also meets the QoS constraints. Moreover, it integrates the strength of PSO and GA. The QoS constraints, such as bandwidth, delay, jitter and interference are transformed into penalty functions. The simulation results show that the hybrid approach outperforms PSO and GA individually, and it takes less convergence time comparatively, keeping away from converging prematurely.

Keywords

  • Wireless mesh networks
  • Multi-radio
  • Multi-channel
  • Particle swarm optimization
  • Genetic algorithm
  • Quality of service
Accesso libero

Designing an Efficient and Extensible Robustness Benchmark of a Real-Time Operating System

Pubblicato online: 13 Mar 2015
Pagine: 84 - 103

Astratto

Abstract

An important step in the development of a Real-Time Operating System (RTOS) is the validation of its tolerance properties. An abnormal input (fault injection) has become one of the most efficient ways to test the software robustness. In this paper we have designed a comprehensive robustness benchmark to evaluate the current popular RTOSs by faults injection. Firstly, we provide a set of uniform application program interfaces to ensure that the benchmark can be easily ported to a new RTOS. Then a package testing method has been used to improve the testing efficiency. Finally, a comprehensive robustness evaluation model is provided for the quantitative evaluation of RTOS robustness. Three popular RTOSs (Ucos2.62, Vxworks5.4 and Rtems4.10) have been evaluated with the help of our benchmark and we have found that Rtems performs best in robust evaluation, while Vxworks performs worst.

Keywords

  • RTOS
  • robustness
  • fault injection
  • package testing
Accesso libero

Business Intelligence Systems for Analyzing University Students Data

Pubblicato online: 13 Mar 2015
Pagine: 104 - 115

Astratto

Abstract

: Globalization and ICT rapid development have led to strong competition between educational institutions. Advanced analytical technologies, including Business Intelligence (BI) tools, are implemented at universities worldwide for analyzing data and getting profound knowledge of the students, their individual learning characteristics and specific educational needs. This paper presents an example of BI implementation for student data analysis.

Parole chiave

  • Business Intelligence
  • university data analysis
  • educational data analysis
Accesso libero

Image Fusion Algorithm Based on Contourlet Transform and PCNN for Detecting Obstacles in Forests

Pubblicato online: 13 Mar 2015
Pagine: 116 - 125

Astratto

Abstract

In this paper the image fusion algorithm based on Contourlet transform and Pulse Coupled Neural Network (PCNN) was proposed to improve the performance of the image fusion in the detection accuracy of obstacles in forests. At the same time, the wavelet transform and the Principal Component Analysis (PCA) were simulated for comparison with the proposed algorithm. Then visible and infrared thermal images were collected in a forest. The experimental results have shown that the fused images using the method proposed provided a better understanding of the reality, enhanced images’ clarity and eliminated factors which provided shelters for targets.

Keywords

  • Contourlet transform
  • image usion
  • obstacles in forests
  • pulse coupled neural network
Accesso libero

A Comparative Analysis of Depth Computation of Leukaemia Images using a Refined Bit Plane and Uncertainty Based Clustering Techniques

Pubblicato online: 13 Mar 2015
Pagine: 126 - 146

Astratto

Abstract

Several image segmentation techniques have been developed over the years to analyze the characteristics of images. Among these, the uncertainty based approaches and their hybrids have been found to be more efficient than the conventional and individual ones. Very recently, a hybrid clustering algorithm, called Rough Intuitionistic Fuzzy C-Means (RIFCM) was proposed by the authors and proved to be more efficient than the conventional and other algorithms applied in this direction, using various datasets. Besides, in order to remove noise from the images, a Refined Bit Plane (RBP) algorithm was introduced by us. In this paper we use a combination of the RBP and RIFCM to propose an approach and apply it to leukemia images. The aim of the paper is twofold. First, it establishes the superiority of our approach in medical diagnosis in comparison to most of the conventional, as well as uncertainty based approaches. The other objective is to provide a computer-aided diagnosis system that will assist the doctors in evaluating medical images in general, and also in easy and better assessment of the disease in leukaemia patients. We have applied several measures like DB-index, D-index, RMSE, PSNR, time estimation in depth computation and histogram analysis to support our conclusions.

Keywords

  • RBP
  • Otsu thresholding
  • histogram analysis
  • RMSE
  • PSNR
  • clustering
  • conventional methods
  • C-Means
  • RIFCM
  • depth computation
  • leukaemia images
11 Articoli
Accesso libero

α-Nearness Ant Colony System with Adaptive Strategies and Performance Analysis

Pubblicato online: 13 Mar 2015
Pagine: 3 - 13

Astratto

Abstract

This paper proposes an improved ant colony system with adaptive strategies, called α

-AACS and considers its performance. First of all, we introduce α-nearness based on the minimum 1-tree for the disadvantage of the Ant Colony System (ACS), which better reflects the chances of a given link, being a member of an optimal tour. Next, we utilize the adaptive operator to balance the population diversity and the convergence speed and propose other optimizations for ACS. Finally, we present an account of the experiments and the statistic-based analysis, which clearly shows that α-AACS has a better global searching ability in finding the best solutions and better performance in solution variation.

Keywords

  • Ant colony system
  • α-nearness
  • minimum 1-tree
  • lower bound
  • adaptive strategy
Accesso libero

A Component Retrieval Tree Matching Algorithm Based on a Faceted Classification Scheme

Pubblicato online: 13 Mar 2015
Pagine: 14 - 23

Astratto

Abstract

An efficient scheme of component retrieval can significantly reduce the cost of software reuse. For this purpose, a method of successfully retrieving of specified components from the component repository is a crucial consideration. However, neither the retrieval efficiency, nor the query-matching rate of the traditional method, which is based on a faceted classification scheme, satisfies the requirements of component retrieval. In this paper a novel component retrieval method combining the features of the faceted classification scheme and the theory of tree matching is proposed. This method not only accurately retrieves components that match queries, but also considers any incomplete descriptions of the retrieval component to completely ensure the relaxation ability of the component retrieval. The experimental results show that the retrieval matching method proposed is highly efficient, and it retrieves feasibly and efficiently the components.

Keywords

  • Component repository
  • component retrieval
  • faceted classification scheme
  • software reuse
  • tree matching
Accesso libero

A Distributed Adaptive Neuro-Fuzzy Network for Chaotic Time Series Prediction

Pubblicato online: 13 Mar 2015
Pagine: 24 - 33

Astratto

Abstract

In this paper a Distributed Adaptive Neuro-Fuzzy Architecture (DANFA) model with a second order Takagi-Sugeno inference mechanism is presented. The proposed approach is based on the simple idea to reduce the number of the fuzzy rules and the computational load, when modeling nonlinear systems. As a learning procedure for the designed structure a two-step gradient descent algorithm with a fixed learning rate is used. To demonstrate the potentials of the selected approach, simulation experiments with two benchmark chaotic time systems − Mackey-Glass and Rossler are studied. The results obtained show an accurate model performance with a minimal prediction error.

Keywords

  • Distributed fuzzy neural network
  • fuzzy-neural models
  • nonlinear identification
  • Takagi-Sugeno fuzzy inference
  • NARX
Accesso libero

Adaptive Fuzzy H Robust Tracking Control for Nonlinear MIMO Systems

Pubblicato online: 13 Mar 2015
Pagine: 34 - 45

Astratto

Abstract

In this paper an adaptive fuzzy H∞ robust tracking control scheme is developed for a class of uncertain nonlinear Multi-Input and Multi-Output (MIMO) systems. Firstly, fuzzy logic systems are introduced to approximate the unknown nonlinear function of the system by an adaptive algorithm. Next, a H∞ robust compensator controller is employed to eliminate the effect of the approximation error and external disturbances. Consequently, a fuzzy adaptive robust controller is proposed, such that the tracking error of the resulting closed-loop system converges to zero and the tracking robustness performance can be guaranteed. The simulation results performed on a two-link robotic manipulator demonstrate the validity of the proposed control scheme.

Keywords

  • Nonlinear MIMO system
  • adaptive fuzzy control
  • H∞ control
Accesso libero

Privacy Preservation of a Group and Secure Data Storage in Cloud Environment

Pubblicato online: 13 Mar 2015
Pagine: 46 - 54

Astratto

Abstract

Cloud computing has become a victorious archetype for data storage, as well as for computation purposes. Greater than ever it concerns user’s privacy, so that data security in a cloud is increasing day by day. Ensuring security and privacy for data organization and query dispensation in the cloud is important for superior and extended uses of cloud based technologies. Cloud users can barely have the full benefits of cloud computing if we can ensure the real user’s privacy and his data security concerns this approach along with storing thin-skinned personal information in databases and software spread around the cloud. There are numerous service suppliers in WWW (World Wide Web), who can supply each service as a cloud. These cloud services will switch over data with a supplementary cloud, so that when the data is exchanged between the clouds, the problem of confidentiality revelation exists. So the privacy revelation problem concerning a person or a corporation is unavoidably open when releasing or data distributing in the cloud service. Confidentiality is a significant issue in any cloud computing environment. In this paper we propose and implement a mechanism to maintain privacy and secure data storage for group members or a community in cloud environment.

Parole chiave

  • Cloud computing
  • privacy
  • data security
  • community
  • GDH
Accesso libero

Public Opinion Evolution Based on Complex Networks

Pubblicato online: 13 Mar 2015
Pagine: 55 - 68

Astratto

Abstract

The Sznajd model of sociophysics can describe the mechanism of making a decision in a closed community. The Complex Agent Networks (CAN) model is studied, based on the adaptability, autonomy and activity of the individuals, as well as the complex interactions of individuals in an open community for probing into evolution of the public opinion. With the help of the theory of complex adaptive systems and the methods of complex networks, the structure of agents, the dynamic networks scenarios and the evolutionary process of the agents are described. The simulation results of CAN model show that all individuals cannot reach a final consensus through mutual consultations when the small world networks rewiring probability p is less than a specified threshold. But when the rewiring probability p is larger than the given threshold, all individuals will eventually come to a finial consensus, and that the rewiring probability p increases, whereas the time of emergence of the public opinion will be significantly reduced. It is quite obvious that in real community the mass media and many other mechanisms have an effect on the evolutionary process of the public opinion.

Keywords

  • Complex networks
  • public opinion
  • complex adaptive systems
  • small world networks
Accesso libero

QoS Guaranteed Intelligent Routing Using Hybrid PSO-GA in Wireless Mesh Networks

Pubblicato online: 13 Mar 2015
Pagine: 69 - 83

Astratto

Abstract

In Multi-Channel Multi-Radio Wireless Mesh Networks (MCMR-WMN), finding the optimal routing by satisfying the Quality of Service (QoS) constraints is an ambitious task. Multiple paths are available from the source node to the gateway for reliability, and sometimes it is necessary to deal with failures of the link in WMN. A major challenge in a MCMR-WMN is finding the routing with QoS satisfied and an interference free path from the redundant paths, in order to transmit the packets through this path. The Particle Swarm Optimization (PSO) is an optimization technique to find the candidate solution in the search space optimally, and it applies artificial intelligence to solve the routing problem. On the other hand, the Genetic Algorithm (GA) is a population based meta-heuristic optimization algorithm inspired by the natural evolution, such as selection, mutation and crossover. PSO can easily fall into a local optimal solution, at the same time GA is not suitable for dynamic data due to the underlying dynamic network. In this paper we propose an optimal intelligent routing, using a Hybrid PSO-GA, which also meets the QoS constraints. Moreover, it integrates the strength of PSO and GA. The QoS constraints, such as bandwidth, delay, jitter and interference are transformed into penalty functions. The simulation results show that the hybrid approach outperforms PSO and GA individually, and it takes less convergence time comparatively, keeping away from converging prematurely.

Keywords

  • Wireless mesh networks
  • Multi-radio
  • Multi-channel
  • Particle swarm optimization
  • Genetic algorithm
  • Quality of service
Accesso libero

Designing an Efficient and Extensible Robustness Benchmark of a Real-Time Operating System

Pubblicato online: 13 Mar 2015
Pagine: 84 - 103

Astratto

Abstract

An important step in the development of a Real-Time Operating System (RTOS) is the validation of its tolerance properties. An abnormal input (fault injection) has become one of the most efficient ways to test the software robustness. In this paper we have designed a comprehensive robustness benchmark to evaluate the current popular RTOSs by faults injection. Firstly, we provide a set of uniform application program interfaces to ensure that the benchmark can be easily ported to a new RTOS. Then a package testing method has been used to improve the testing efficiency. Finally, a comprehensive robustness evaluation model is provided for the quantitative evaluation of RTOS robustness. Three popular RTOSs (Ucos2.62, Vxworks5.4 and Rtems4.10) have been evaluated with the help of our benchmark and we have found that Rtems performs best in robust evaluation, while Vxworks performs worst.

Keywords

  • RTOS
  • robustness
  • fault injection
  • package testing
Accesso libero

Business Intelligence Systems for Analyzing University Students Data

Pubblicato online: 13 Mar 2015
Pagine: 104 - 115

Astratto

Abstract

: Globalization and ICT rapid development have led to strong competition between educational institutions. Advanced analytical technologies, including Business Intelligence (BI) tools, are implemented at universities worldwide for analyzing data and getting profound knowledge of the students, their individual learning characteristics and specific educational needs. This paper presents an example of BI implementation for student data analysis.

Parole chiave

  • Business Intelligence
  • university data analysis
  • educational data analysis
Accesso libero

Image Fusion Algorithm Based on Contourlet Transform and PCNN for Detecting Obstacles in Forests

Pubblicato online: 13 Mar 2015
Pagine: 116 - 125

Astratto

Abstract

In this paper the image fusion algorithm based on Contourlet transform and Pulse Coupled Neural Network (PCNN) was proposed to improve the performance of the image fusion in the detection accuracy of obstacles in forests. At the same time, the wavelet transform and the Principal Component Analysis (PCA) were simulated for comparison with the proposed algorithm. Then visible and infrared thermal images were collected in a forest. The experimental results have shown that the fused images using the method proposed provided a better understanding of the reality, enhanced images’ clarity and eliminated factors which provided shelters for targets.

Keywords

  • Contourlet transform
  • image usion
  • obstacles in forests
  • pulse coupled neural network
Accesso libero

A Comparative Analysis of Depth Computation of Leukaemia Images using a Refined Bit Plane and Uncertainty Based Clustering Techniques

Pubblicato online: 13 Mar 2015
Pagine: 126 - 146

Astratto

Abstract

Several image segmentation techniques have been developed over the years to analyze the characteristics of images. Among these, the uncertainty based approaches and their hybrids have been found to be more efficient than the conventional and individual ones. Very recently, a hybrid clustering algorithm, called Rough Intuitionistic Fuzzy C-Means (RIFCM) was proposed by the authors and proved to be more efficient than the conventional and other algorithms applied in this direction, using various datasets. Besides, in order to remove noise from the images, a Refined Bit Plane (RBP) algorithm was introduced by us. In this paper we use a combination of the RBP and RIFCM to propose an approach and apply it to leukemia images. The aim of the paper is twofold. First, it establishes the superiority of our approach in medical diagnosis in comparison to most of the conventional, as well as uncertainty based approaches. The other objective is to provide a computer-aided diagnosis system that will assist the doctors in evaluating medical images in general, and also in easy and better assessment of the disease in leukaemia patients. We have applied several measures like DB-index, D-index, RMSE, PSNR, time estimation in depth computation and histogram analysis to support our conclusions.

Keywords

  • RBP
  • Otsu thresholding
  • histogram analysis
  • RMSE
  • PSNR
  • clustering
  • conventional methods
  • C-Means
  • RIFCM
  • depth computation
  • leukaemia images

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