1. Queen’s University, Kingston, Canada
Image Steganography Using Fuzzy Domain Transformation and Pixel Classification
Aleem Khalid Alvi
Robin Dawes
School of Computing
Queen’s University, Kingston, Canada

2. Contents Information Hiding Methods Proposed Technique
Fuzzy Image Representation and Domain Transformation
Gaussian Membership Function (GMF)
Fuzzy Inference System (FIS)
Methodology
Using Image Processing for Fuzzy Pixel Classification
Analysis and Results
Conclusion

3. Information Hiding Methods
Attributes for classification of information hiding methods
Cover objects
Secret objects
Hiding techniques
Current technologies
Steganography system characteristics
Robustness
Security
Un-detectability
Imperceptibility (invisibility or perceptual transparency)
High capacity

4. Proposed Technique Proposed technique is the combination of
Domain transformation
Data conversion
Substitution
Image properties
It is kind of private-key steganography technique

5. Fuzzy Image Representation and Domain Transformation
An image representation in spatial and fuzzy

6. Gaussian Membership Function (GMF)
We use GMF for image
transformation from the
spatial domain into the
fuzzy domain
The specific image transformation function with fuzzifier
Where fh = fuzzifier, Imax = maximum pixel value of an image,
Imn = any gray level pixel value of an image I

7. Fuzzy Inference System (FIS)
We use Mamdani fuzzy interference system (FIS)
Using the fuzzy inference process,
A given input (a crisp input) maps to an output (a crisp output) using fuzzy logic methods.
The fuzzy inference process requires membership functions, logical operations, and If-Then rules.
Implementation steps
Fuzzify inputs
Apply fuzzy operator
Apply implication method
Aggregate all outputs
Defuzzify

8. Methodology
The step-by-step methodological information for embedding process on the sending end of the steganography System.

9. Using Image Processing for Fuzzy Pixel Classification
Use fuzzy based If-Then rules to apply fuzzy classification
Select the appropriate cover pixel for embedding secret data
Produce less disturbance and distortion in the embedded cover image with respect to Human Visual System (HVS)
Use texture and silhouette (edge) properties of an image

10. Analysis and Results Using Lena (Cover) and
Tomahawk Missile (Secret) Images
Lena.jpg available capacity
= 145,313 pixels
Secret data uses 17.62% of the
available capacity
HVS testing shows that original
and stego images have significant
difference and visible as light shades
Statistical testing shows differences
Cover histograms looks similar

11. Analysis and Results contd..
Using Baboon (Cover) and
Tomahawk Missile (Secret) Images
Baboon.jpg has available capacity
= 138,518 pixels
Uses 18.48% available capacity
HVS testing shows that no
difference in visibility
Statistical testing shows the
difference between their statistical
values
Cover histograms looks similar

12. Conclusion
Proposed steganography algorithm based on fuzzy inference system
Fuzzy inference system uses fuzzy transformation and pixel classification techniques
The fuzzy pixel classification uses the image processing techniques by exploiting texture and silhouette properties
The exploitation of the image processing techniques with fuzzy logic increase imperceptibility in stego image significantly

13. Thank You!