Framework for Watermark Robustness Adjustment

Framework for Watermark Robustness Adjustment Using Image Depth Map Hoda Mohaghegh, Nader Karimi and Shadrokh Samavi Mohaghegh, H.; Karimi, N.; Samavi, S., “Framework for Watermark Robustness Adjustment Using Image Depth Map,” Proceedings of Iranian Conference on Electrical Engineering (ICEE), May 2015.

Outline

● Introduction ● Proposed Method ● Experimental Results ● Conclusion

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Introduction Explosion in the use of digital multimedia

The enforcement of multimedia copyright protection

Digital watermarking 3

Introduction

Watermark Embedding

Secret Key

Watermarked Image

Original Watermark

Sender

Attack/ Distortion in Channel

Original Image

Secret Key

Distorted Watermarked Image Receiver

Watermark Extraction

Recovered Watermark

General Model of Watermarking System

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Introduction  Requirements on watermarking :

• Imperceptibility • Robustness • Security • Capacity 5

Introduction  Tradeoff between Imperceptibility and Robustness

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Introduction  Watermarking Methods Classification Based on:

Spatial

● Domain

● Adaptivity

Frequency

Adaptive Non Adaptive 7

Input Image

Proposed Method Embedding Scheme

16x16 Blocking

Depth Estimation

Bi Foreground / Background Separation

4x4 Blocking Bi1

Bi16 SVD

SVD

16x16 Blocking

S11

S11 DCT

Alpha Selection

DCT Coefficients Modification

Inverse DCT S’11 Inverse SVD

S’11 Inverse SVD

B’i1

B’i16

Sub block retiling B’i Block retiling Watermarked Image

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Proposed Method  DCT Coefficients Modification

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Proposed Method  Depth Estimation and Foreground/Background Separation

Original Image¹

Depth Map¹

FG/BG Map

10 ¹.http://vision.middlebury.edu/.

Proposed Method 

• •

•

Extraction Scheme Extraction procedure is completely blind, including: Partitioning SVD – DCT formation Watermark reconstruction based on the following rule:

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Experimental Results  Evaluation Metrics

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Experimental Results  Evaluation Metrics

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Experimental Results  Perceptual Quality - Objective Visual Quality Metric

Ours

Method [17]

PSNR

40.27

40.89

DBPSNR

44.91

42.57

14 [17] H. Guan, Z. Zeng, J. Liu, S. Zhang, and P. Guo, “A novel geometrically invariant blind robust watermarking algorithm based on SVD and DCT,” International Conference on Image Analysis and Signal Processing (IASP), pp. 1-5, 2012.

Experimental Results  Perceptual Quality - Subjective

Ours

Method [17]

15 [17] H. Guan, Z. Zeng, J. Liu, S. Zhang, and P. Guo, “A novel geometrically invariant blind robust watermarking algorithm based on SVD and DCT,” International Conference on Image Analysis and Signal Processing (IASP), pp. 1-5, 2012.

Experimental Results  Robustness – BER of extracted watermark

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[17] H. Guan, Z. Zeng, J. Liu, S. Zhang, and P. Guo, “A novel geometrically invariant blind robust watermarking algorithm based on SVD and DCT,” International Conference on Image Analysis and Signal Processing (IASP), pp. 1-5, 2012.

Experimental Results  Robustness – BER of extracted watermark Attacks

Attack’s parameter

Variance = 0.01 Variance = 0.02 Scaling Factor = 10 Scaling Factor = 25 Scaling Scaling Factor = 50 Scaling Factor = 75 Scaling Factor = 125 Window Size = 3 Window Size = 5 Median Filter Window Size = 7 Window Size = 9 Window Size = 11 AWGN

Ours 0.040 0.046 0.500 0.0015 0 0 0 0 0.0104 0.0766 0.3601 0.5402

BER Method [17] 0.0860 0.0900 0.5491 0.0871 0.0060 0 0 0.0060 0.0588 0.2381 0.4457 0.4985

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[17] H. Guan, Z. Zeng, J. Liu, S. Zhang, and P. Guo, “A novel geometrically invariant blind robust watermarking algorithm based on SVD and DCT,” International Conference on Image Analysis and Signal Processing (IASP), pp. 1-5, 2012.

Experimental Results  Perceptual Quality – PSNR and DBPSNR Adaptive Method PSNR = 34.92 DBPSNR = 44.40 BER = 0

Non-Adaptive Method PSNR = 35.65 DBPSNR= 42.55

BER = 0

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Conclusion ● Using

hybrid procedure.

SVD-DCT

domain

for

embedding

● Depth as an adaptivity factor for controlling the strength

of embedding. ● A proper tradeoff between visual quality of watermarked

images with respect to Human Visual system and robustness.

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