SlideShare a Scribd company logo
Reversible Data Hiding With Optimal Value Transfer
ABSTRACT:
In reversible data hiding techniques, the values of host data are modified according to some
particular rules and the original host content can be perfectly restored after extraction of the
hidden data on receiver side. In this paper, the optimal rule of value modification under a
payload-distortion criterion is found by using an iterative procedure, and a practical reversible
data hiding scheme is proposed. The secret data, as well as the auxiliary information used for
content recovery, are carried by the differences between the original pixel-values and the
corresponding values estimated from the neighbors. Here, the estimation errors are modified
according to the optimal value transfer rule. Also, the host image is divided into a number of
pixel subsets and the auxiliary information of a subset is always embedded into the estimation
errors in the next subset. A receiver can successfully extract the embedded secret data and
recover the original content in the subsets with an inverse order. This way, a good reversible
data hiding performance is achieved.
EXISTING SYSTEM:
GLOBALSOFT TECHNOLOGIES
IEEE PROJECTS & SOFTWARE DEVELOPMENTS
IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE
BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS
CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401
Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmail.com
A data-hider can also employ histogram modification mechanism to realize reversible data
hiding. In the host image is divided into blocks sized 4 ×4, 8 ×8, or 16 ×16, and gray values are
mapped to a circle. After pseudo-randomly segmenting each block into two sub-regions,
rotation of the histograms of the two sub-regions on this circle is used to embed one bit in each
block. On the receiving side, the original block can be recovered from a marked image in an
inverse process. Payload of this method is low since each block can only carry one bit. Based
on this method, a robust lossless data hiding scheme is proposed, which can be used for semi-
fragile image authentication. A typical HM method presented for utilizes the zero and peak
points of the histogram of an image and slightly modifies the pixel grayscale values to embed
data into the image. In binary tree structure is used to eliminate the requirement to communicate
pairs of peak and zero points to the recipient, and a histogram shifting technique is adopted to
prevent overflow and underflow. The histogram modification mechanism can also be
implemented in the difference between sub-sampled images and the prediction error of host
pixels and several good prediction approaches have been introduced to improve the
performance of reversible data hiding.
DISADVANTAGES OF EXISTING SYSTEM:
 In these reversible data hiding methods, a spare place can always be made available to
accommodate secret data as long as the chosen item is compressible, but the capacities
are not very high.
 Payload of this method is low since each block can only carry one bit.
PROPOSED SYSTEM:
In this paper, we will find the optimal rule of value modification under a payload-distortion
criterion. By maximizing a target function using iterative algorithm, an optimal value transfer
matrix can be obtained. Furthermore, we design a practical reversible data hiding scheme, in
which the estimation errors of host pixels are used to accommodate the secret data and their
values are modified according to the optimal value transfer matrix. This way, a good payload-
distortion performance can be achieved
ADVANTAGES OF PROPOSED SYSTEM:
 A smarter prediction method is exploited to make the estimation errors closer to zero, a
better performance can be achieved, but the computation complexity due to the prediction
will be higher.
 The payload-distortion performance of the proposed scheme is excellent.
 The host image is divided into a number of subsets and the auxiliary information of a
subset is always embedded into the estimation errors in the next subset. This way, one
can successfully extract the embedded secret data and recover the original content in the
subsets with an inverse order.
SYSTEM CONFIGURATION:-
HARDWARE REQUIREMENTS:-
 Processor - Pentium –IV
 Speed - 1.1 Ghz
 RAM - 256 MB(min)
 Hard Disk - 20 GB
 Key Board - Standard Windows Keyboard
 Mouse - Two or Three Button Mouse
 Monitor - SVGA
SOFTWARE REQUIREMENTS:
• Operating system : - Windows XP.
• Coding Language : C#.Net
REFERENCE:
Xinpeng Zhang, Member, IEEE “Reversible Data Hiding With Optimal Value Transfer” IEEE
TRANSACTIONS ON MULTIMEDIA, VOL. 15, NO. 2, FEBRUARY 2013.
CLOUING
DOMAIN: WIRELESS NETWORK PROJECTS

More Related Content

What's hot

SW_BigData
SW_BigDataSW_BigData
SW_BigData
Mohammed Shoaib
 
Investigation and Evaluation of Microgrid Optimization Techniques
Investigation and Evaluation of Microgrid Optimization TechniquesInvestigation and Evaluation of Microgrid Optimization Techniques
Investigation and Evaluation of Microgrid Optimization Techniques
Nevin Sawyer
 
Target Response Electrical usage Profile Clustering using Big Data
Target Response Electrical usage Profile Clustering using Big DataTarget Response Electrical usage Profile Clustering using Big Data
Target Response Electrical usage Profile Clustering using Big Data
IRJET Journal
 
A general weighted_fuzzy_clustering_algorithm
A general weighted_fuzzy_clustering_algorithmA general weighted_fuzzy_clustering_algorithm
A general weighted_fuzzy_clustering_algorithm
TA Minh Thuy
 
G018134149
G018134149G018134149
G018134149
IOSR Journals
 
Crop classification using supervised learning techniques
Crop classification using supervised learning techniquesCrop classification using supervised learning techniques
Crop classification using supervised learning techniques
Northeastern Univeristy
 
Joint Approach of Routing , Rate Adaptation and Power Control in Wireless Mes...
Joint Approach of Routing , Rate Adaptation and Power Control in Wireless Mes...Joint Approach of Routing , Rate Adaptation and Power Control in Wireless Mes...
Joint Approach of Routing , Rate Adaptation and Power Control in Wireless Mes...
Manjunath Badiger
 
Joint Approach of Routing , Rate Adaptation and Power Control in Wireless Mes...
Joint Approach of Routing , Rate Adaptation and Power Control in Wireless Mes...Joint Approach of Routing , Rate Adaptation and Power Control in Wireless Mes...
Joint Approach of Routing , Rate Adaptation and Power Control in Wireless Mes...
Manjunath Badiger
 
FrackingPaper
FrackingPaperFrackingPaper
FrackingPaper
Collin Purcell
 
Deep Learning Fast MRI Using Channel Attention in Magnitude Domain
Deep Learning Fast MRI Using Channel Attention in Magnitude DomainDeep Learning Fast MRI Using Channel Attention in Magnitude Domain
Deep Learning Fast MRI Using Channel Attention in Magnitude Domain
Joonhyung Lee
 
Measurement Of Rn222 Concentrations In The Air Of Peshraw & Darbandikhan Tu...
Measurement Of Rn222  Concentrations In The Air Of Peshraw &  Darbandikhan Tu...Measurement Of Rn222  Concentrations In The Air Of Peshraw &  Darbandikhan Tu...
Measurement Of Rn222 Concentrations In The Air Of Peshraw & Darbandikhan Tu...
IJMER
 
IEEE SSCI 2011 Talk - Neural Networks Ensembles for Short-Term Load Forecasting
IEEE SSCI 2011 Talk - Neural Networks Ensembles for Short-Term Load ForecastingIEEE SSCI 2011 Talk - Neural Networks Ensembles for Short-Term Load Forecasting
IEEE SSCI 2011 Talk - Neural Networks Ensembles for Short-Term Load Forecasting
matteodefelice
 
Advanced Techniques for Mobile Robotics
Advanced Techniques for Mobile RoboticsAdvanced Techniques for Mobile Robotics
Advanced Techniques for Mobile Robotics
Prasanth Jaya
 
Electricity Demand Forecasting Using Fuzzy-Neural Network
Electricity Demand Forecasting Using Fuzzy-Neural NetworkElectricity Demand Forecasting Using Fuzzy-Neural Network
Electricity Demand Forecasting Using Fuzzy-Neural Network
Naren Chandra Kattla
 
Electricity Demand Forecasting Using ANN
Electricity Demand Forecasting Using ANNElectricity Demand Forecasting Using ANN
Electricity Demand Forecasting Using ANN
Naren Chandra Kattla
 
post119s1-file3
post119s1-file3post119s1-file3
post119s1-file3
Venkata Suhas Maringanti
 
Power system transient stability margin estimation using artificial neural ne...
Power system transient stability margin estimation using artificial neural ne...Power system transient stability margin estimation using artificial neural ne...
Power system transient stability margin estimation using artificial neural ne...
elelijjournal
 
Adaptive Training of Radial Basis Function Networks Based on Cooperative
Adaptive Training of Radial Basis Function Networks Based on CooperativeAdaptive Training of Radial Basis Function Networks Based on Cooperative
Adaptive Training of Radial Basis Function Networks Based on Cooperative
ESCOM
 
Ay33292297
Ay33292297Ay33292297
Ay33292297
IJERA Editor
 

What's hot (19)

SW_BigData
SW_BigDataSW_BigData
SW_BigData
 
Investigation and Evaluation of Microgrid Optimization Techniques
Investigation and Evaluation of Microgrid Optimization TechniquesInvestigation and Evaluation of Microgrid Optimization Techniques
Investigation and Evaluation of Microgrid Optimization Techniques
 
Target Response Electrical usage Profile Clustering using Big Data
Target Response Electrical usage Profile Clustering using Big DataTarget Response Electrical usage Profile Clustering using Big Data
Target Response Electrical usage Profile Clustering using Big Data
 
A general weighted_fuzzy_clustering_algorithm
A general weighted_fuzzy_clustering_algorithmA general weighted_fuzzy_clustering_algorithm
A general weighted_fuzzy_clustering_algorithm
 
G018134149
G018134149G018134149
G018134149
 
Crop classification using supervised learning techniques
Crop classification using supervised learning techniquesCrop classification using supervised learning techniques
Crop classification using supervised learning techniques
 
Joint Approach of Routing , Rate Adaptation and Power Control in Wireless Mes...
Joint Approach of Routing , Rate Adaptation and Power Control in Wireless Mes...Joint Approach of Routing , Rate Adaptation and Power Control in Wireless Mes...
Joint Approach of Routing , Rate Adaptation and Power Control in Wireless Mes...
 
Joint Approach of Routing , Rate Adaptation and Power Control in Wireless Mes...
Joint Approach of Routing , Rate Adaptation and Power Control in Wireless Mes...Joint Approach of Routing , Rate Adaptation and Power Control in Wireless Mes...
Joint Approach of Routing , Rate Adaptation and Power Control in Wireless Mes...
 
FrackingPaper
FrackingPaperFrackingPaper
FrackingPaper
 
Deep Learning Fast MRI Using Channel Attention in Magnitude Domain
Deep Learning Fast MRI Using Channel Attention in Magnitude DomainDeep Learning Fast MRI Using Channel Attention in Magnitude Domain
Deep Learning Fast MRI Using Channel Attention in Magnitude Domain
 
Measurement Of Rn222 Concentrations In The Air Of Peshraw & Darbandikhan Tu...
Measurement Of Rn222  Concentrations In The Air Of Peshraw &  Darbandikhan Tu...Measurement Of Rn222  Concentrations In The Air Of Peshraw &  Darbandikhan Tu...
Measurement Of Rn222 Concentrations In The Air Of Peshraw & Darbandikhan Tu...
 
IEEE SSCI 2011 Talk - Neural Networks Ensembles for Short-Term Load Forecasting
IEEE SSCI 2011 Talk - Neural Networks Ensembles for Short-Term Load ForecastingIEEE SSCI 2011 Talk - Neural Networks Ensembles for Short-Term Load Forecasting
IEEE SSCI 2011 Talk - Neural Networks Ensembles for Short-Term Load Forecasting
 
Advanced Techniques for Mobile Robotics
Advanced Techniques for Mobile RoboticsAdvanced Techniques for Mobile Robotics
Advanced Techniques for Mobile Robotics
 
Electricity Demand Forecasting Using Fuzzy-Neural Network
Electricity Demand Forecasting Using Fuzzy-Neural NetworkElectricity Demand Forecasting Using Fuzzy-Neural Network
Electricity Demand Forecasting Using Fuzzy-Neural Network
 
Electricity Demand Forecasting Using ANN
Electricity Demand Forecasting Using ANNElectricity Demand Forecasting Using ANN
Electricity Demand Forecasting Using ANN
 
post119s1-file3
post119s1-file3post119s1-file3
post119s1-file3
 
Power system transient stability margin estimation using artificial neural ne...
Power system transient stability margin estimation using artificial neural ne...Power system transient stability margin estimation using artificial neural ne...
Power system transient stability margin estimation using artificial neural ne...
 
Adaptive Training of Radial Basis Function Networks Based on Cooperative
Adaptive Training of Radial Basis Function Networks Based on CooperativeAdaptive Training of Radial Basis Function Networks Based on Cooperative
Adaptive Training of Radial Basis Function Networks Based on Cooperative
 
Ay33292297
Ay33292297Ay33292297
Ay33292297
 

Similar to JAVA 2013 IEEE IMAGEPROCESSING PROJECT Reversible data hiding with optimal value transfer

Reversible data hiding with optimal value transfer
Reversible data hiding with optimal value transferReversible data hiding with optimal value transfer
Reversible data hiding with optimal value transfer
Ecway Technologies
 
Matlab reversible data hiding with optimal value transfer
Matlab  reversible data hiding with optimal value transferMatlab  reversible data hiding with optimal value transfer
Matlab reversible data hiding with optimal value transfer
Ecway Technologies
 
REVERSIBLE DATA HIDING WITH GOOD PAYLOAD DISTORTIONPpt 3
REVERSIBLE DATA HIDING WITH GOOD PAYLOAD DISTORTIONPpt 3 REVERSIBLE DATA HIDING WITH GOOD PAYLOAD DISTORTIONPpt 3
REVERSIBLE DATA HIDING WITH GOOD PAYLOAD DISTORTIONPpt 3
Parthipan Parthi
 
Reversible Image Data Hiding with Contrast Enhancement
Reversible Image Data Hiding with Contrast EnhancementReversible Image Data Hiding with Contrast Enhancement
Reversible Image Data Hiding with Contrast Enhancement
IRJET Journal
 
An enhanced difference pair mapping steganography method to improve embedding...
An enhanced difference pair mapping steganography method to improve embedding...An enhanced difference pair mapping steganography method to improve embedding...
An enhanced difference pair mapping steganography method to improve embedding...
eSAT Publishing House
 
IRJET- Encryption and Authentication of Image by using Data Hiding
IRJET- Encryption and Authentication of Image by using Data HidingIRJET- Encryption and Authentication of Image by using Data Hiding
IRJET- Encryption and Authentication of Image by using Data Hiding
IRJET Journal
 
Reversible image data hiding with contrast enhancement
Reversible image data hiding with contrast enhancementReversible image data hiding with contrast enhancement
Reversible image data hiding with contrast enhancement
redpel dot com
 
Segmentation of Images by using Fuzzy k-means clustering with ACO
Segmentation of Images by using Fuzzy k-means clustering with ACOSegmentation of Images by using Fuzzy k-means clustering with ACO
Segmentation of Images by using Fuzzy k-means clustering with ACO
IJTET Journal
 
K041068072
K041068072K041068072
K041068072
ijceronline
 
JPM1416 A Unified Data Embedding and Scrambling Method
JPM1416   A Unified Data Embedding and Scrambling MethodJPM1416   A Unified Data Embedding and Scrambling Method
JPM1416 A Unified Data Embedding and Scrambling Method
chennaijp
 
Reversible Data Hiding in Encrypted color images by Reserving Room before Enc...
Reversible Data Hiding in Encrypted color images by Reserving Room before Enc...Reversible Data Hiding in Encrypted color images by Reserving Room before Enc...
Reversible Data Hiding in Encrypted color images by Reserving Room before Enc...
ijceronline
 
98462-234458-1-PB
98462-234458-1-PB98462-234458-1-PB
98462-234458-1-PB
Dinesh Kannan
 
Id62
Id62Id62
Id62
IJEEE
 
A new hybrid steganographic method for histogram preservation
A new hybrid steganographic method for histogram preservation A new hybrid steganographic method for histogram preservation
A new hybrid steganographic method for histogram preservation
IJEEE
 
Data Hiding Using Reversibly Designed Difference-Pair Method
Data Hiding Using Reversibly Designed Difference-Pair MethodData Hiding Using Reversibly Designed Difference-Pair Method
Data Hiding Using Reversibly Designed Difference-Pair Method
IJERA Editor
 
A New Chaos Based Image Encryption and Decryption using a Hash Function
A New Chaos Based Image Encryption and Decryption using a Hash FunctionA New Chaos Based Image Encryption and Decryption using a Hash Function
A New Chaos Based Image Encryption and Decryption using a Hash Function
IRJET Journal
 
IEEE 2014 Matlab Projects
IEEE 2014 Matlab ProjectsIEEE 2014 Matlab Projects
IEEE 2014 Matlab Projects
Vijay Karan
 
IEEE 2014 Matlab Projects
IEEE 2014 Matlab ProjectsIEEE 2014 Matlab Projects
IEEE 2014 Matlab Projects
Vijay Karan
 
Efficient Reversible Data Hiding Algorithms Based on Dual Prediction
Efficient Reversible Data Hiding Algorithms Based on Dual PredictionEfficient Reversible Data Hiding Algorithms Based on Dual Prediction
Efficient Reversible Data Hiding Algorithms Based on Dual Prediction
sipij
 
Ay33292297
Ay33292297Ay33292297
Ay33292297
IJERA Editor
 

Similar to JAVA 2013 IEEE IMAGEPROCESSING PROJECT Reversible data hiding with optimal value transfer (20)

Reversible data hiding with optimal value transfer
Reversible data hiding with optimal value transferReversible data hiding with optimal value transfer
Reversible data hiding with optimal value transfer
 
Matlab reversible data hiding with optimal value transfer
Matlab  reversible data hiding with optimal value transferMatlab  reversible data hiding with optimal value transfer
Matlab reversible data hiding with optimal value transfer
 
REVERSIBLE DATA HIDING WITH GOOD PAYLOAD DISTORTIONPpt 3
REVERSIBLE DATA HIDING WITH GOOD PAYLOAD DISTORTIONPpt 3 REVERSIBLE DATA HIDING WITH GOOD PAYLOAD DISTORTIONPpt 3
REVERSIBLE DATA HIDING WITH GOOD PAYLOAD DISTORTIONPpt 3
 
Reversible Image Data Hiding with Contrast Enhancement
Reversible Image Data Hiding with Contrast EnhancementReversible Image Data Hiding with Contrast Enhancement
Reversible Image Data Hiding with Contrast Enhancement
 
An enhanced difference pair mapping steganography method to improve embedding...
An enhanced difference pair mapping steganography method to improve embedding...An enhanced difference pair mapping steganography method to improve embedding...
An enhanced difference pair mapping steganography method to improve embedding...
 
IRJET- Encryption and Authentication of Image by using Data Hiding
IRJET- Encryption and Authentication of Image by using Data HidingIRJET- Encryption and Authentication of Image by using Data Hiding
IRJET- Encryption and Authentication of Image by using Data Hiding
 
Reversible image data hiding with contrast enhancement
Reversible image data hiding with contrast enhancementReversible image data hiding with contrast enhancement
Reversible image data hiding with contrast enhancement
 
Segmentation of Images by using Fuzzy k-means clustering with ACO
Segmentation of Images by using Fuzzy k-means clustering with ACOSegmentation of Images by using Fuzzy k-means clustering with ACO
Segmentation of Images by using Fuzzy k-means clustering with ACO
 
K041068072
K041068072K041068072
K041068072
 
JPM1416 A Unified Data Embedding and Scrambling Method
JPM1416   A Unified Data Embedding and Scrambling MethodJPM1416   A Unified Data Embedding and Scrambling Method
JPM1416 A Unified Data Embedding and Scrambling Method
 
Reversible Data Hiding in Encrypted color images by Reserving Room before Enc...
Reversible Data Hiding in Encrypted color images by Reserving Room before Enc...Reversible Data Hiding in Encrypted color images by Reserving Room before Enc...
Reversible Data Hiding in Encrypted color images by Reserving Room before Enc...
 
98462-234458-1-PB
98462-234458-1-PB98462-234458-1-PB
98462-234458-1-PB
 
Id62
Id62Id62
Id62
 
A new hybrid steganographic method for histogram preservation
A new hybrid steganographic method for histogram preservation A new hybrid steganographic method for histogram preservation
A new hybrid steganographic method for histogram preservation
 
Data Hiding Using Reversibly Designed Difference-Pair Method
Data Hiding Using Reversibly Designed Difference-Pair MethodData Hiding Using Reversibly Designed Difference-Pair Method
Data Hiding Using Reversibly Designed Difference-Pair Method
 
A New Chaos Based Image Encryption and Decryption using a Hash Function
A New Chaos Based Image Encryption and Decryption using a Hash FunctionA New Chaos Based Image Encryption and Decryption using a Hash Function
A New Chaos Based Image Encryption and Decryption using a Hash Function
 
IEEE 2014 Matlab Projects
IEEE 2014 Matlab ProjectsIEEE 2014 Matlab Projects
IEEE 2014 Matlab Projects
 
IEEE 2014 Matlab Projects
IEEE 2014 Matlab ProjectsIEEE 2014 Matlab Projects
IEEE 2014 Matlab Projects
 
Efficient Reversible Data Hiding Algorithms Based on Dual Prediction
Efficient Reversible Data Hiding Algorithms Based on Dual PredictionEfficient Reversible Data Hiding Algorithms Based on Dual Prediction
Efficient Reversible Data Hiding Algorithms Based on Dual Prediction
 
Ay33292297
Ay33292297Ay33292297
Ay33292297
 

More from IEEEGLOBALSOFTTECHNOLOGIES

DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Vampire attacks draining life from w...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Vampire attacks draining life from w...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Vampire attacks draining life from w...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Vampire attacks draining life from w...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT SSD a robust rf location fingerprint...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT SSD a robust rf location fingerprint...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT SSD a robust rf location fingerprint...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT SSD a robust rf location fingerprint...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Privacy preserving distributed profi...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Privacy preserving distributed profi...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Privacy preserving distributed profi...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Privacy preserving distributed profi...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Optimal multicast capacity and delay...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Optimal multicast capacity and delay...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Optimal multicast capacity and delay...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Optimal multicast capacity and delay...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Model based analysis of wireless sys...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Model based analysis of wireless sys...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Model based analysis of wireless sys...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Model based analysis of wireless sys...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Mobile relay configuration in data i...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Mobile relay configuration in data i...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Mobile relay configuration in data i...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Mobile relay configuration in data i...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Distributed cooperative caching in s...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Distributed cooperative caching in s...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Distributed cooperative caching in s...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Distributed cooperative caching in s...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Delay optimal broadcast for multihop...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Delay optimal broadcast for multihop...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Delay optimal broadcast for multihop...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Delay optimal broadcast for multihop...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Dcim distributed cache invalidation ...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Dcim distributed cache invalidation ...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Dcim distributed cache invalidation ...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Dcim distributed cache invalidation ...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Cooperative packet delivery in hybri...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Cooperative packet delivery in hybri...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Cooperative packet delivery in hybri...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Cooperative packet delivery in hybri...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone base...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone base...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone base...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone base...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Capacity of hybrid wireless mesh net...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Capacity of hybrid wireless mesh net...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Capacity of hybrid wireless mesh net...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Capacity of hybrid wireless mesh net...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Adaptive position update for geograp...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Adaptive position update for geograp...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Adaptive position update for geograp...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Adaptive position update for geograp...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT A scalable server architecture for m...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT A scalable server architecture for m...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT A scalable server architecture for m...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT A scalable server architecture for m...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...
IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Qos ranking prediction for cloud serv...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Qos ranking prediction for cloud serv...DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Qos ranking prediction for cloud serv...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Qos ranking prediction for cloud serv...
IEEEGLOBALSOFTTECHNOLOGIES
 

More from IEEEGLOBALSOFTTECHNOLOGIES (20)

DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Vampire attacks draining life from w...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Vampire attacks draining life from w...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Vampire attacks draining life from w...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Vampire attacks draining life from w...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT SSD a robust rf location fingerprint...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT SSD a robust rf location fingerprint...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT SSD a robust rf location fingerprint...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT SSD a robust rf location fingerprint...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Privacy preserving distributed profi...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Privacy preserving distributed profi...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Privacy preserving distributed profi...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Privacy preserving distributed profi...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Optimal multicast capacity and delay...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Optimal multicast capacity and delay...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Optimal multicast capacity and delay...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Optimal multicast capacity and delay...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Model based analysis of wireless sys...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Model based analysis of wireless sys...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Model based analysis of wireless sys...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Model based analysis of wireless sys...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Mobile relay configuration in data i...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Mobile relay configuration in data i...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Mobile relay configuration in data i...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Mobile relay configuration in data i...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Distributed cooperative caching in s...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Distributed cooperative caching in s...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Distributed cooperative caching in s...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Distributed cooperative caching in s...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Delay optimal broadcast for multihop...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Delay optimal broadcast for multihop...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Delay optimal broadcast for multihop...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Delay optimal broadcast for multihop...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Dcim distributed cache invalidation ...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Dcim distributed cache invalidation ...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Dcim distributed cache invalidation ...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Dcim distributed cache invalidation ...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Cooperative packet delivery in hybri...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Cooperative packet delivery in hybri...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Cooperative packet delivery in hybri...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Cooperative packet delivery in hybri...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone base...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone base...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone base...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone base...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Capacity of hybrid wireless mesh net...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Capacity of hybrid wireless mesh net...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Capacity of hybrid wireless mesh net...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Capacity of hybrid wireless mesh net...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Adaptive position update for geograp...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Adaptive position update for geograp...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Adaptive position update for geograp...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Adaptive position update for geograp...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT A scalable server architecture for m...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT A scalable server architecture for m...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT A scalable server architecture for m...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT A scalable server architecture for m...
 
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
 
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
 
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...
 
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Qos ranking prediction for cloud serv...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Qos ranking prediction for cloud serv...DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Qos ranking prediction for cloud serv...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Qos ranking prediction for cloud serv...
 

Recently uploaded

Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)
Jakub Marek
 
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptxNordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
MichaelKnudsen27
 
Trusted Execution Environment for Decentralized Process Mining
Trusted Execution Environment for Decentralized Process MiningTrusted Execution Environment for Decentralized Process Mining
Trusted Execution Environment for Decentralized Process Mining
LucaBarbaro3
 
AWS Cloud Cost Optimization Presentation.pptx
AWS Cloud Cost Optimization Presentation.pptxAWS Cloud Cost Optimization Presentation.pptx
AWS Cloud Cost Optimization Presentation.pptx
HarisZaheer8
 
Taking AI to the Next Level in Manufacturing.pdf
Taking AI to the Next Level in Manufacturing.pdfTaking AI to the Next Level in Manufacturing.pdf
Taking AI to the Next Level in Manufacturing.pdf
ssuserfac0301
 
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdfMonitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Tosin Akinosho
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
Zilliz
 
Serial Arm Control in Real Time Presentation
Serial Arm Control in Real Time PresentationSerial Arm Control in Real Time Presentation
Serial Arm Control in Real Time Presentation
tolgahangng
 
UI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentationUI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentation
Wouter Lemaire
 
Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxOcean lotus Threat actors project by John Sitima 2024 (1).pptx
Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
SitimaJohn
 
Skybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoptionSkybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoption
Tatiana Kojar
 
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
saastr
 
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success StoryDriving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Safe Software
 
Building Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and MilvusBuilding Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and Milvus
Zilliz
 
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing InstancesEnergy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Alpen-Adria-Universität
 
Fueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte WebinarFueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte Webinar
Zilliz
 
Skybuffer AI: Advanced Conversational and Generative AI Solution on SAP Busin...
Skybuffer AI: Advanced Conversational and Generative AI Solution on SAP Busin...Skybuffer AI: Advanced Conversational and Generative AI Solution on SAP Busin...
Skybuffer AI: Advanced Conversational and Generative AI Solution on SAP Busin...
Tatiana Kojar
 
Operating System Used by Users in day-to-day life.pptx
Operating System Used by Users in day-to-day life.pptxOperating System Used by Users in day-to-day life.pptx
Operating System Used by Users in day-to-day life.pptx
Pravash Chandra Das
 
Generating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and MilvusGenerating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and Milvus
Zilliz
 
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
shyamraj55
 

Recently uploaded (20)

Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)
 
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptxNordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
 
Trusted Execution Environment for Decentralized Process Mining
Trusted Execution Environment for Decentralized Process MiningTrusted Execution Environment for Decentralized Process Mining
Trusted Execution Environment for Decentralized Process Mining
 
AWS Cloud Cost Optimization Presentation.pptx
AWS Cloud Cost Optimization Presentation.pptxAWS Cloud Cost Optimization Presentation.pptx
AWS Cloud Cost Optimization Presentation.pptx
 
Taking AI to the Next Level in Manufacturing.pdf
Taking AI to the Next Level in Manufacturing.pdfTaking AI to the Next Level in Manufacturing.pdf
Taking AI to the Next Level in Manufacturing.pdf
 
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdfMonitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdf
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
 
Serial Arm Control in Real Time Presentation
Serial Arm Control in Real Time PresentationSerial Arm Control in Real Time Presentation
Serial Arm Control in Real Time Presentation
 
UI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentationUI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentation
 
Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxOcean lotus Threat actors project by John Sitima 2024 (1).pptx
Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
 
Skybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoptionSkybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoption
 
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
 
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success StoryDriving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
 
Building Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and MilvusBuilding Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and Milvus
 
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing InstancesEnergy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
 
Fueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte WebinarFueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte Webinar
 
Skybuffer AI: Advanced Conversational and Generative AI Solution on SAP Busin...
Skybuffer AI: Advanced Conversational and Generative AI Solution on SAP Busin...Skybuffer AI: Advanced Conversational and Generative AI Solution on SAP Busin...
Skybuffer AI: Advanced Conversational and Generative AI Solution on SAP Busin...
 
Operating System Used by Users in day-to-day life.pptx
Operating System Used by Users in day-to-day life.pptxOperating System Used by Users in day-to-day life.pptx
Operating System Used by Users in day-to-day life.pptx
 
Generating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and MilvusGenerating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and Milvus
 
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
 

JAVA 2013 IEEE IMAGEPROCESSING PROJECT Reversible data hiding with optimal value transfer

  • 1. Reversible Data Hiding With Optimal Value Transfer ABSTRACT: In reversible data hiding techniques, the values of host data are modified according to some particular rules and the original host content can be perfectly restored after extraction of the hidden data on receiver side. In this paper, the optimal rule of value modification under a payload-distortion criterion is found by using an iterative procedure, and a practical reversible data hiding scheme is proposed. The secret data, as well as the auxiliary information used for content recovery, are carried by the differences between the original pixel-values and the corresponding values estimated from the neighbors. Here, the estimation errors are modified according to the optimal value transfer rule. Also, the host image is divided into a number of pixel subsets and the auxiliary information of a subset is always embedded into the estimation errors in the next subset. A receiver can successfully extract the embedded secret data and recover the original content in the subsets with an inverse order. This way, a good reversible data hiding performance is achieved. EXISTING SYSTEM: GLOBALSOFT TECHNOLOGIES IEEE PROJECTS & SOFTWARE DEVELOPMENTS IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401 Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmail.com
  • 2. A data-hider can also employ histogram modification mechanism to realize reversible data hiding. In the host image is divided into blocks sized 4 ×4, 8 ×8, or 16 ×16, and gray values are mapped to a circle. After pseudo-randomly segmenting each block into two sub-regions, rotation of the histograms of the two sub-regions on this circle is used to embed one bit in each block. On the receiving side, the original block can be recovered from a marked image in an inverse process. Payload of this method is low since each block can only carry one bit. Based on this method, a robust lossless data hiding scheme is proposed, which can be used for semi- fragile image authentication. A typical HM method presented for utilizes the zero and peak points of the histogram of an image and slightly modifies the pixel grayscale values to embed data into the image. In binary tree structure is used to eliminate the requirement to communicate pairs of peak and zero points to the recipient, and a histogram shifting technique is adopted to prevent overflow and underflow. The histogram modification mechanism can also be implemented in the difference between sub-sampled images and the prediction error of host pixels and several good prediction approaches have been introduced to improve the performance of reversible data hiding. DISADVANTAGES OF EXISTING SYSTEM:  In these reversible data hiding methods, a spare place can always be made available to accommodate secret data as long as the chosen item is compressible, but the capacities are not very high.  Payload of this method is low since each block can only carry one bit. PROPOSED SYSTEM: In this paper, we will find the optimal rule of value modification under a payload-distortion criterion. By maximizing a target function using iterative algorithm, an optimal value transfer matrix can be obtained. Furthermore, we design a practical reversible data hiding scheme, in which the estimation errors of host pixels are used to accommodate the secret data and their
  • 3. values are modified according to the optimal value transfer matrix. This way, a good payload- distortion performance can be achieved ADVANTAGES OF PROPOSED SYSTEM:  A smarter prediction method is exploited to make the estimation errors closer to zero, a better performance can be achieved, but the computation complexity due to the prediction will be higher.  The payload-distortion performance of the proposed scheme is excellent.  The host image is divided into a number of subsets and the auxiliary information of a subset is always embedded into the estimation errors in the next subset. This way, one can successfully extract the embedded secret data and recover the original content in the subsets with an inverse order. SYSTEM CONFIGURATION:- HARDWARE REQUIREMENTS:-  Processor - Pentium –IV  Speed - 1.1 Ghz  RAM - 256 MB(min)  Hard Disk - 20 GB  Key Board - Standard Windows Keyboard  Mouse - Two or Three Button Mouse  Monitor - SVGA
  • 4. SOFTWARE REQUIREMENTS: • Operating system : - Windows XP. • Coding Language : C#.Net REFERENCE: Xinpeng Zhang, Member, IEEE “Reversible Data Hiding With Optimal Value Transfer” IEEE TRANSACTIONS ON MULTIMEDIA, VOL. 15, NO. 2, FEBRUARY 2013.