Digital Image Watermarking Er-Hsien Fu EE381K-15280 Student Presentation.

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Digital Image Watermarking

Er-Hsien Fu

EE381K-15280

Student Presentation

Overview• Introduction

• Background

Watermark Properties

Embedding

Detection

• The Project

Introduction

Embedding

Detection

• Conclusions

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

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

W=[1 0 0 1 0 0 1 1 0 1 1 1 0 1 0 0 1 1 1 1 0 1 0 0 0]

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

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

Setup-Watermark Embedding

Image1000 Highest Coeff

ConvCode

DCT

Inter-leave

Water-mark

Water-markedImage

IDCT

•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

Original Image Watermarked Image, No Coding

Watermarked Image with Coding

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

Watermark Detection

* =

Suspected Image ExtractedWatermark

Original Watermark

Correlation

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

Watermark Detection

CorruptedImage

OriginalImage

Extracted Watermark

Owner’swatermark

CorrelationCoefficient

1000 HighestDCT Coeff

Deinterleave,Viterbi Decode

•For no coding, deinterleave and decode block ignored=E[W1*W2]/{ E[W12]E[W22]}•If W1=W2 then =1•if W1 and W2 are independent, then =0 if E[W1]=0•Corruptions are additive noise, JPEG CompressionImage scaling, and UnZign

W2

W1

Convolutional Codes

Input=[...1011010101100000000]G0 = [1 1 1 1 0 1 0 1 1]G1 = [1 0 1 1 1 0 0 0 1]

C0

C1

•Output C0 = conv(G0,Input); Output C1=conv(G1,Input)•Convolutional code implemented using linear shift registers•Adds redundancy for error-correction•Encoding/Decoding well researched•Good coding performance, very popular

Viterbi Decoding0123

State

…………

•Find most likely path through trellis

•Begin and end at all zero state

•Upper arrows => input=0, Lower arrow =>input=1

•Every possible input/output combination is compared with the received output

•Optimal Decoding Method

With Coding:Additive Noise (0,900)

No Coding:Additive Noise(0,900)

•Zero mean additive noise, variance=100, 400, 900•Both methods had high correlation•Coding method performed slightly better•For variance = 900 (no coding) = 77%p (coding) = 84%

4:1 JPEG Compression,No coding

4:1 JPEG CompressionWith Coding

•JPEG Compression: 1.4:1, 2.2:1, 4:1 ratio•Both methods resistant to JPEG compression•Coding method outperformed non-coding method•Perfect detection for coding method

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

Conclusions

•Convolutional coding more immune to additive noise andJPEG Compression•Coding method fragile w.r.t. rescaled images•Moderate detection levels for unzigned images•Further Suggestion:Try block DCTUse Wavelet TransformExploit Human Visual System

Questions