This Paper Presents An Improved Secure Reversible Data Hiding Scheme In Encrypted Images Based On Integer Transformation, Which Does Not Need Using A Data Hider Key To Protect The Embedded Secret Data. We First Segment The Original Image Into Blocks Of Various Sizes Based On The Quadtree-based Image Partition. For Each Block, We Reserve M Least Significant Bits (LSBs) Of Each Pixel As Embedding Room Based On The Reversible Integer Transformation. In Order To Improve The Security Of The Image Encryption, We Pad The MLSBs Of Each Pixel Using The Corresponding (8-m) Most Significant Bits (MSBs) Information After The Transformation, Which Protects The Security Of The Encryption Key. Then, We Encrypt The Transformed Image With A Standard Stream Cipher. After The Image Encryption, The Data Hider Embeds The Secret Data In The MLSBs Of The Encrypted Images Through An Exclusive Or Operation. On The Receiving Side, The Receiver Can Extract The Secret Data After The Image Decryption And Recover The Original Image Without Loss Of Quality. The Security Analysis Shows That The Proposed Scheme Improves The Security Weakness Of The Scheme Directly Using Adaptive Integer Transformation. The Experimental Results Show That The Proposed Method Achieves A Higher Embedding Ratio Compared With Several Relevant Methods.
Steganography Is Defined As The Science Of Hiding Or Embedding “data” In A Transmission Medium. Its Ultimate Objectives, Which Are Undetectability, Robustness (i.e., Against Image Processing And Other Attacks) And Capacity Of The Hidden Data (i.e., How Much Data We Can Hide In The Carrier File), Are The Main Factors That Distinguish It From Other “sisters-in Science” Techniques, Namely Watermarking And Cryptography. This Paper Provides An Overview Of Well Known Steganography Methods. It Identifies Current Research Problems In This Area And Discusses How Our Current Research Approach Could Solve Some Of These Problems. We Propose Using Human Skin Tone Detection In Colour Images To Form An Adaptive Context For An Edge Operator Which Will Provide An Excellent Secure Location For Data Hiding.
The Main Aim Of The Proposed Securing The Transmission Between Sender And Receiver. The Input Text Data Applied The Encoded Data. This Present Method That Combine The Secret Message And Data Hiding Technique, Encryption And Decryption Transmission Purpose. In This Method We Embed The Original Data With Secure Information By Using Lossless Data Hiding Method Then Apply Encryption Algorithm Of Both Input And Secret Message Is Completely Encrypted After That For More Security And Cover Completely Encrypted .We Apply Cryptography By Text Of Any Other Secrete Text .In Receiver Side, When The Message Is Arrived Then We Apply The Inverse Methods In Reverse Order To Get The Denoised Original Text And Secret Information. We Have Applied And Showed The Results Of Our Method To Texts.
Despite The Progress In Digital Image Watermarking Technology, The Main Objectives Of The Majority Of Research In This Area Remain To Be The Improvement In Robustness To Attack. In This Paper, A Novel Watermarking Technique Is Proposed Using A Region-adaptive Approach To Further Improve Upon Criteria. Watermark Data Is Embedded On Different Regions Of The Host Image Using A Combination Of Discrete Wavelet Transform And Singular Value Decomposition Techniques. The Technique Is Derived From An Earlier Hypothesis That The Robustness Of A Watermarking Process Can Be Improved By Using Watermark Data Which Frequency Spectrum Not Dissimilar To That Of The Host Data. To Facilitate This, The Technique Utilises Dual Watermarking Technologies And Embed Parts Of The Watermark Images Into Selected Regions In The Host Image. Our Experiment Shows Our Technique Has Improved The Robustness Of The Watermark Data To Image Processing Attacks And Geometric Attacks, Thus Validating The Earlier Hypothesis.
Secure Data Communication Is The Most Important And Essential Issue In The Area Of Message Transmission Over The Networks. Cryptography Provides The Way Of Making Secure Message For Confidential Message Transfer. Cryptography Is The Process Of Transforming The Sender's Message To A Secret Format Called Cipher Text That Only Intended Receiver Will Get Understand The Meaning Of The Secret Message. There Are Various Cryptographic Or DNA Based Encoding Algorithms Have Been Proposed In Order To Make Secret Message For Communication. But All These Proposed DNA Based Encryption Algorithms Are Not Secure Enough To Provide Better Security As Compared With The Today's Security Requirement. In This Paper, We Have Proposed A Technique Of Encryption That Will Enhance The Message Security. In This Proposed Algorithm, A New Method Of DNA Based Encryption With A Strong Key Of 256 Bit Is Used. Along With This Big Size Key Various Other Encoding Tools Are Used As Key In The Encoding Process Of The Message Like Random Series Of DNA Bases, Modified DNA Bases Coding. Moreover A New Method Of Round Key Selection Is Also Given In This Paper To Provide Better Security In The Message. The Cipher Text Contains The Extra Bit Of Information As Similar With The DNA Strands That Will Provide Better And Enhanced Security Against Intruder's Attack.
Data Detection Using SMVQ And Noise Reduction
Natural Image Statistics Plays An Important Role In Image Denoising, And Various Natural Image Priors, Including Gradient-based, Sparse Representation-based, And Nonlocal Self-similarity-based Ones, Have Been Widely Studied And Exploited For Noise Removal. In Spite Of The Great Success Of Many Denoising Algorithms, They Tend To Smooth The Fine Scale Image Textures When Removing Noise, Degrading The Image Visual Quality. To Address This Problem, In This Paper, We Propose A Texture Enhanced Image Denoising Method By Enforcing The Gradient Histogram Of The Denoised Image To Be Close To A Reference Gradient Histogram Of The Original Image. Given The Reference Gradient Histogram, A Novel Gradient Histogram Preservation (GHP) Algorithm Is Developed To Enhance The Texture Structures While Removing Noise. Two Region-based Variants Of GHP Are Proposed For The Denoising Of Images Consisting Of Regions With Different Textures. An Algorithm Is Also Developed To Effectively Estimate The Reference Gradient Histogram From The Noisy Observation Of The Unknown Image. Our Experimental Results Demonstrate That The Proposed GHP Algorithm Can Well Preserve The Texture Appearance In The Denoised Images, Making Them Look More Natural.
We do code in Matlab for all domains, Image Processing, Simulink Design and Power Electronics.
Our Complete portfolio describes how stuff we are watch our demo @ Youtube Link.
2024 © All Rights Reserved. Site Map