SlideShare une entreprise Scribd logo
1  sur  15
Guided by
Problem Definition

 When ever we transmit the data(image) in the
 network, any unauthenticated person can read our
 data(image).

 In order to provide security to data(image) generally
 sender will encrypt the data(image) and send it the
 intended person and the receiver will decrypt the
 encrypted data(image) and uses it
Background Introduction
 Extended Visual Cryptography schemes.

 The existing system does not provide a friendly
 environment to encrypt or decrypt the data (images).

 Deals only with binary input share images.

 A larger pixel expansion value.

 It uses access structure or threshold access structure
Proposed System
 Proposed system Visual cryptography provides a
 friendly environment to deal with images.

 Deal with Gray scale input images.

 A minimum pixel expansion.

 It uses general access structure.
Use case diagram
Administrator



            Login                   login



Create
 user                     Change
           Delete        password
            user
Converting color image to binary
     start j
                                     If
                                  value>           no
 Input image                        122
                               yes
                                              Img(I,J)=0

W=width(img)                   Img(I,J)=255
H=height(img)

                                  Next J
  for I=1 to W

                                  Next I
   for J=1 o H
                                 Output
                                  img
    Value=Get
Brightness(P(I,J))
                                  Stop
Share creation using halftone algorithm

                                            If
      Start                             Img(I,J)<
                                          black
  Let Img=input
       image
                        temp(JX2,IX2)=black      temp(JX2,IX2)=black
  W=width(Img)        temp(JX2,IX2H)=white     temp(JX2,IX2H)=white
  H=height(Img)       temp(JX299,IX2)=white    temp(JX299,IX2)=white
                     temp(JX299,IX2H)=black   temp(JX299,IX2H)=black
     Create
temp(width,height)

                         Output           Next J
  for I=0 to H-1
                          Img
                                                      Next I
   For J0 to W-1          Stop
Algorithm2: Halftonig process
Input : The c x d dithering matrix D and a pixel with
        gray-level g in input image I.
Output: The halftoned pattern at the position of the
        pixel
        For i=0 to c-1 do
        For j=0 to d-1 to do
              If g<=Dij then
        print a black pixel at position (i,j);
              Else
        print a white pixel at position (i,j);
Algorithm 3: Embedding process
Input : The covering shares constructed in Section IV, the
           corresponding VCS with pixel expansion and the
           secret image .
Output: The embedded shares .
Step 1: Dividing the covering shares into blocks that contain
          subpixels each.
Step 2: Choose embedding positions in each block in the
          covering shares.
Step 3: For each black (respectively, white) pixel in,randomly
         choose a share matrix (respectively).
Step 4: Embed the subpixels of each row of the share
       matrix into the embedding positions chosen in
        Step 2.
Embedding process
          Start
                                                for I=1 to w-1

          Input
        Img1,Img2                               for J=1 to H-1


W1=width(Img1) width(Img2)                   Out(I,J)=Img1(I,J) or
H1=height(Img1)height(Img2)                       Img2(I,J)


         If w1=w2                  Output           Next J
                              No
            and                    process
          H1=H2                     fails
                                                    Next I
        yes
                                   Stop
        W=W1=W2
         H=H1=H2                                     Stop
Snap Shots
Work completed and future work
Conclusion
Progre  ppt

Contenu connexe

Tendances

Image Restoration (Digital Image Processing)
Image Restoration (Digital Image Processing)Image Restoration (Digital Image Processing)
Image Restoration (Digital Image Processing)VARUN KUMAR
 
Computer Graphics - Introduction in Brief By: Prof. Manisha Waghmare- Butkar
Computer Graphics - Introduction in Brief By: Prof. Manisha Waghmare- ButkarComputer Graphics - Introduction in Brief By: Prof. Manisha Waghmare- Butkar
Computer Graphics - Introduction in Brief By: Prof. Manisha Waghmare- ButkarVishal Butkar
 
Digital image processing using matlab: basic transformations, filters and ope...
Digital image processing using matlab: basic transformations, filters and ope...Digital image processing using matlab: basic transformations, filters and ope...
Digital image processing using matlab: basic transformations, filters and ope...thanh nguyen
 
Linear programming graphical method
Linear programming graphical methodLinear programming graphical method
Linear programming graphical methodDr. Abdulfatah Salem
 
Dynamic Feature Induction: The Last Gist to the State-of-the-Art
Dynamic Feature Induction: The Last Gist to the State-of-the-ArtDynamic Feature Induction: The Last Gist to the State-of-the-Art
Dynamic Feature Induction: The Last Gist to the State-of-the-ArtJinho Choi
 
A few solvers for portfolio selection
A few solvers for portfolio selectionA few solvers for portfolio selection
A few solvers for portfolio selectionBogusz Jelinski
 
Introduction to operations research
Introduction to operations researchIntroduction to operations research
Introduction to operations researchDr. Abdulfatah Salem
 
Image enhancement using alpha rooting based hybrid technique
Image enhancement using alpha rooting based hybrid techniqueImage enhancement using alpha rooting based hybrid technique
Image enhancement using alpha rooting based hybrid techniqueRahul Yadav
 
Non Deterministic and Deterministic Problems
Non Deterministic and Deterministic Problems Non Deterministic and Deterministic Problems
Non Deterministic and Deterministic Problems Scandala Tamang
 
COMPUTER GRAPHICS
COMPUTER GRAPHICSCOMPUTER GRAPHICS
COMPUTER GRAPHICSJagan Raja
 
Lesson 28: The Fundamental Theorem of Calculus
Lesson 28: The Fundamental Theorem of CalculusLesson 28: The Fundamental Theorem of Calculus
Lesson 28: The Fundamental Theorem of CalculusMatthew Leingang
 

Tendances (20)

Image Restoration (Digital Image Processing)
Image Restoration (Digital Image Processing)Image Restoration (Digital Image Processing)
Image Restoration (Digital Image Processing)
 
Computer Graphics - Introduction in Brief By: Prof. Manisha Waghmare- Butkar
Computer Graphics - Introduction in Brief By: Prof. Manisha Waghmare- ButkarComputer Graphics - Introduction in Brief By: Prof. Manisha Waghmare- Butkar
Computer Graphics - Introduction in Brief By: Prof. Manisha Waghmare- Butkar
 
Digital image processing using matlab: basic transformations, filters and ope...
Digital image processing using matlab: basic transformations, filters and ope...Digital image processing using matlab: basic transformations, filters and ope...
Digital image processing using matlab: basic transformations, filters and ope...
 
Linear programming graphical method
Linear programming graphical methodLinear programming graphical method
Linear programming graphical method
 
Pixelrelationships
PixelrelationshipsPixelrelationships
Pixelrelationships
 
Dynamic Feature Induction: The Last Gist to the State-of-the-Art
Dynamic Feature Induction: The Last Gist to the State-of-the-ArtDynamic Feature Induction: The Last Gist to the State-of-the-Art
Dynamic Feature Induction: The Last Gist to the State-of-the-Art
 
A few solvers for portfolio selection
A few solvers for portfolio selectionA few solvers for portfolio selection
A few solvers for portfolio selection
 
Mathematical tools in dip
Mathematical tools in dipMathematical tools in dip
Mathematical tools in dip
 
Introduction to operations research
Introduction to operations researchIntroduction to operations research
Introduction to operations research
 
Image enhancement using alpha rooting based hybrid technique
Image enhancement using alpha rooting based hybrid techniqueImage enhancement using alpha rooting based hybrid technique
Image enhancement using alpha rooting based hybrid technique
 
Graphics file
Graphics fileGraphics file
Graphics file
 
Basis grafik
Basis grafikBasis grafik
Basis grafik
 
Eigenfaces
EigenfacesEigenfaces
Eigenfaces
 
Non Deterministic and Deterministic Problems
Non Deterministic and Deterministic Problems Non Deterministic and Deterministic Problems
Non Deterministic and Deterministic Problems
 
Calc 4.1b
Calc 4.1bCalc 4.1b
Calc 4.1b
 
COMPUTER GRAPHICS
COMPUTER GRAPHICSCOMPUTER GRAPHICS
COMPUTER GRAPHICS
 
Lesson 28: The Fundamental Theorem of Calculus
Lesson 28: The Fundamental Theorem of CalculusLesson 28: The Fundamental Theorem of Calculus
Lesson 28: The Fundamental Theorem of Calculus
 
Dip3
Dip3Dip3
Dip3
 
Image enhancement
Image enhancementImage enhancement
Image enhancement
 
Basis graphics
Basis graphicsBasis graphics
Basis graphics
 

En vedette

Visual Cryptography in Meaningful Shares
Visual Cryptography in Meaningful SharesVisual Cryptography in Meaningful Shares
Visual Cryptography in Meaningful SharesDebarko De
 
Extended Visual Cryptography Using Watermarking
Extended Visual Cryptography Using WatermarkingExtended Visual Cryptography Using Watermarking
Extended Visual Cryptography Using WatermarkingShivam Singh
 
Visual Cryptography
Visual CryptographyVisual Cryptography
Visual CryptographyAneeshGKumar
 
Cloud computing for agent based urban transportation system vinayss
Cloud computing for agent based urban transportation system vinayssCloud computing for agent based urban transportation system vinayss
Cloud computing for agent based urban transportation system vinayssVinay Sirivara
 

En vedette (7)

Visual cryptography1
Visual cryptography1Visual cryptography1
Visual cryptography1
 
Visual CryptoGraphy
Visual CryptoGraphyVisual CryptoGraphy
Visual CryptoGraphy
 
Visual Cryptography in Meaningful Shares
Visual Cryptography in Meaningful SharesVisual Cryptography in Meaningful Shares
Visual Cryptography in Meaningful Shares
 
Extended Visual Cryptography Using Watermarking
Extended Visual Cryptography Using WatermarkingExtended Visual Cryptography Using Watermarking
Extended Visual Cryptography Using Watermarking
 
Visual Cryptography
Visual CryptographyVisual Cryptography
Visual Cryptography
 
Cloud computing for agent based urban transportation system vinayss
Cloud computing for agent based urban transportation system vinayssCloud computing for agent based urban transportation system vinayss
Cloud computing for agent based urban transportation system vinayss
 
Visual Cryptography
Visual CryptographyVisual Cryptography
Visual Cryptography
 

Similaire à Progre ppt (8)

DIP-Enhancement-Spatial.pptx
DIP-Enhancement-Spatial.pptxDIP-Enhancement-Spatial.pptx
DIP-Enhancement-Spatial.pptx
 
Basics of Computer graphics lab
Basics of Computer graphics labBasics of Computer graphics lab
Basics of Computer graphics lab
 
chapter-2 SPACIAL DOMAIN.pptx
chapter-2 SPACIAL DOMAIN.pptxchapter-2 SPACIAL DOMAIN.pptx
chapter-2 SPACIAL DOMAIN.pptx
 
Computer graphics
Computer graphics   Computer graphics
Computer graphics
 
Computer graphics
Computer graphics   Computer graphics
Computer graphics
 
Dip iit workshop
Dip iit workshopDip iit workshop
Dip iit workshop
 
image_enhancement_spatial
 image_enhancement_spatial image_enhancement_spatial
image_enhancement_spatial
 
Point Processing
Point ProcessingPoint Processing
Point Processing
 

Progre ppt

  • 2. Problem Definition  When ever we transmit the data(image) in the network, any unauthenticated person can read our data(image).  In order to provide security to data(image) generally sender will encrypt the data(image) and send it the intended person and the receiver will decrypt the encrypted data(image) and uses it
  • 3. Background Introduction  Extended Visual Cryptography schemes.  The existing system does not provide a friendly environment to encrypt or decrypt the data (images).  Deals only with binary input share images.  A larger pixel expansion value.  It uses access structure or threshold access structure
  • 4. Proposed System  Proposed system Visual cryptography provides a friendly environment to deal with images.  Deal with Gray scale input images.  A minimum pixel expansion.  It uses general access structure.
  • 6. Administrator Login login Create user Change Delete password user
  • 7. Converting color image to binary start j If value> no Input image 122 yes Img(I,J)=0 W=width(img) Img(I,J)=255 H=height(img) Next J for I=1 to W Next I for J=1 o H Output img Value=Get Brightness(P(I,J)) Stop
  • 8. Share creation using halftone algorithm If Start Img(I,J)< black Let Img=input image temp(JX2,IX2)=black temp(JX2,IX2)=black W=width(Img) temp(JX2,IX2H)=white temp(JX2,IX2H)=white H=height(Img) temp(JX299,IX2)=white temp(JX299,IX2)=white temp(JX299,IX2H)=black temp(JX299,IX2H)=black Create temp(width,height) Output Next J for I=0 to H-1 Img Next I For J0 to W-1 Stop
  • 9. Algorithm2: Halftonig process Input : The c x d dithering matrix D and a pixel with gray-level g in input image I. Output: The halftoned pattern at the position of the pixel For i=0 to c-1 do For j=0 to d-1 to do If g<=Dij then print a black pixel at position (i,j); Else print a white pixel at position (i,j);
  • 10. Algorithm 3: Embedding process Input : The covering shares constructed in Section IV, the corresponding VCS with pixel expansion and the secret image . Output: The embedded shares . Step 1: Dividing the covering shares into blocks that contain subpixels each. Step 2: Choose embedding positions in each block in the covering shares. Step 3: For each black (respectively, white) pixel in,randomly choose a share matrix (respectively). Step 4: Embed the subpixels of each row of the share matrix into the embedding positions chosen in Step 2.
  • 11. Embedding process Start for I=1 to w-1 Input Img1,Img2 for J=1 to H-1 W1=width(Img1) width(Img2) Out(I,J)=Img1(I,J) or H1=height(Img1)height(Img2) Img2(I,J) If w1=w2 Output Next J No and process H1=H2 fails Next I yes Stop W=W1=W2 H=H1=H2 Stop
  • 13. Work completed and future work