Digital%20Image%20Watermarking

1
Digital Image Watermarking

• Er-Hsien Fu
• EE381K-15280
• Student Presentation

2
Overview

• Introduction
• Background
• Watermark Properties
• Embedding
• Detection
• The Project
• Introduction
• Embedding
• Detection
• Conclusions

3
Introduction

• Watermark--an invisible signature embedded inside
  an image to show authenticity or proof of
  ownership
• Discourage unauthorized copying and distribution
  of images over the internet
• Ensure a digital picture has not been altered
• Software can be used to search for a specific
  watermark

4
BackgroundWatermark Properties

• Watermark should appear random, noise-like
  sequence
• Appear Undetectable
• Good Correlation Properties
• High correlation with signals similar to
  watermark
• Low correlation with other watermarks or random
  noise
• Common sequences
• A) Normal distribution
• B) m-sequences

W1 0 0 1 0 0 1 1 0 1 1 1 0 1 0
0 1 1 1 1 0 1 0 0 0
5
Project Introduction

• Possible for watermark to be binary sequence
• Error-correction coding techniques
• Use convolutional codes
• Decode by Viterbi algorithm
• Compare with non-coding method
• See if it improves watermark detection
• More or less robust to attacks?
• Additive noise, JPEG Compression, Rescale,
• Unzign
• Performance assessed by correlation coefficient

6
Watermark Embedding
Watermark
Original Image
Watermarked image

• Watermark placed into information content of
  Original Image to create
• Watermarked Image
• Image Content
• Spatial Domain (Least Significant Bit)
• FFT - Magnitude and Phase
• Wavelet Transforms
• DCT Coefficients

7
Setup-Watermark Embedding
DCT
IDCT
1000 Highest Coeff
Water- marked Image
Image
Inter- leave
Conv Code
Water- mark

• DC Component Excluded for 1000 Highest
  Coefficients
• Interleaving prevents burst errors
• Watermarked Image Similar to original image
• Without coding, ignore Conv Code and Interleave
  block

8
Original Image
Watermarked Image, No Coding

• 512x512 Mandrill Image
• See Handout
• Both watermarks imperceptible
• Alterations to original image
• difficult to notice

Watermarked Image with Coding
9
Watermark Detection
?

Extracted Watermark
Original Watermark
Suspected Image
Correlation

• Watermark Extracted from Suspected Image
• Compute correlation of Extracted and Original
  Watermark
• Threshold correlation to determine watermark
  existence

10
Watermark Detection
W2
Correlation Coefficient
Deinterleave, Viterbi Decode
Corrupted Image
Extracted Watermark
W1
Original Image
1000 Highest DCT Coeff
Owners watermark

• For no coding, deinterleave and decode block
  ignored
• ?EW1W2/ EW12EW22
• If W1W2 then ?1
• if W1 and W2 are independent, then ?0 if EW10
• Corruptions are additive noise, JPEG Compression
• Image scaling, and UnZign

11
Convolutional Codes
C0
Input...1011010101100000000 G0 1 1 1 1 0 1
0 1 1 G1 1 0 1 1 1 0 0 0 1
C1

• Output C0 conv(G0,Input) Output
  C1conv(G1,Input)
• Convolutional code implemented using linear shift
  registers
• Adds redundancy for error-correction
• Encoding/Decoding well researched
• Good coding performance, very popular

12
Viterbi Decoding
State
0

1
2
3

• Find most likely path through trellis
• Begin and end at all zero state
• Upper arrows gt input0, Lower arrow gtinput1
• Every possible input/output combination is
  compared with the received output
• Optimal Decoding Method

13
With Coding Additive Noise (0,900)
No Coding Additive Noise(0,900)

• Zero mean additive noise, variance100, 400, 900
• Both methods had high correlation
• Coding method performed slightly better
• For variance 900
• ? (no coding) 77
• p (coding) 84

14
41 JPEG Compression, No coding
41 JPEG Compression With Coding

• JPEG Compression 1.41, 2.21, 41 ratio
• Both methods resistant to JPEG compression
• Coding method outperformed non-coding method
• Perfect detection for coding method

15
Watermark removal using Unzign
Convert to grayscale and resize

• Unzign--watermark removal software
• Image resized to 512x512 and convert to grayscale
  before detection
• Moderate detection for without coding
• ?(no coding) 57
• ?(coding) 23
• Coding method sensitive to resizing

16
Conclusions

• Convolutional coding more immune to additive
  noise and
• JPEG Compression
• Coding method fragile w.r.t. rescaled images
• Moderate detection levels for unzigned images
• Further Suggestion
• Try block DCT
• Use Wavelet Transform
• Exploit Human Visual System

17
Questions