Robustness Studies For a Multi-Mode Information Embedding Scheme for Digital Images Daniel Eliades...
-
Upload
augustus-tyler -
Category
Documents
-
view
214 -
download
0
Transcript of Robustness Studies For a Multi-Mode Information Embedding Scheme for Digital Images Daniel Eliades...
Robustness Studies
For a Multi-Mode Information Embedding Scheme for Digital Images
Daniel EliadesMentor: Dr. Neelu Sinha
Department of Math and Computer Science, Fairleigh Dickinson University
Fairleigh Dickinson University Dainel Eliades 2
Contents
Introduction & Background of Digital Watermarking
Overview of a Watermarking technique based upon Adaptive Segmentation and Space-Frequency Representation (WASSFR)
Robustness Studies
JPEG Compression
Fairleigh Dickinson University Dainel Eliades 3
Introduction & Background
Extensive use and distribution of digitized media in the Internet Age.
Need for WASSFR to protect, detect and verifyownership of data.
Affirmed by the US Digital Millennium Copyright Act (DCMA), enacted into law in October 1998.
Fairleigh Dickinson University Dainel Eliades 4
Background
Principles in the Design of a Watermarking Algorithm
Imperceptibility
Robustness/Redundancy Must be robust to signal processing distortions
& attacks
Fairleigh Dickinson University Dainel Eliades 5
Watermarking Scheme
Watermark (W)
Original Data (I)
Key (k)
Watermarked Data (I’)
Watermark Insertion
Digital Watermark
Fairleigh Dickinson University Dainel Eliades 6
Watermarking Scheme
Digital Watermark
Watermark (W) or Original Data (I)
Watermarked Data (I’)
Key (k)
Confidence Measure or Watermark (W)
Watermark Detection
Fairleigh Dickinson University Dainel Eliades 7
Overview of WASSFR
Watermarking technique based upon Adaptive Segmentation and Space-Frequency representation
Need for WASSFR to protect, detect and verify ownership of data.
Extensive use and distribution of digitized media in the Internet Age.
Fairleigh Dickinson University Dainel Eliades 8
Adaptive segmentation of the image based on a novel “entropy” criterion.
Selection of a suitable space-frequency representation for each segment To allow for highest watermark bit rate
Identification of perceptually most significant component in the transformed image
Insertion of the Watermark
Overview of WASSFR (cont).
Fairleigh Dickinson University Dainel Eliades 9
Separation of an image into regions with similar attribute: in terms of susceptibility to distortions in space and frequency domain
Uniform intensity or textured regions less affected by controlled noise injection in frequency domain
Edges less affected if noise profile is controllable in space domain
Perceptually significant components are easier to identify for a suitably segmented image
Adaptive Segmentation
Fairleigh Dickinson University Dainel Eliades 10
Instead of using pure frequency domain approach (as used by Cox et al.) use a set of space-frequency representations
Space representation If entropy <= T1
2-D Frequency representation (DCT) If T2 < entropy
2-D Wavelet representation If T1 < entropy <= T2
Space-Frequency Representation
Fairleigh Dickinson University Dainel Eliades 11
Robustness/Bit error rate measurement
Robustness measured in terms of bit error rate, -the number of information bits which may be received corrupt for a single information bit.
Studied as a function of data throughput (bitrate in bits/pixel)
Robustness Studies
Fairleigh Dickinson University Dainel Eliades 12
Selection of an Image Database
Size of data and nature of data both have an impact on the robustness
Various classes of images used
Attacks
Geometric and removal attacks
Robustness Studies (cont.)
Fairleigh Dickinson University Dainel Eliades 13
Data Throughput – the number of embedded bits of information while keeping the perceptual distortion and detection ambiguity below desired thresholds.
A higher data throughput allows for better cryptography as well as powerful channel coding.
In practice, available data throughput tempered by the overhead required to achieve a desired level of robustness.
Performance MetricData Throughput vs.
Robustness
Fairleigh Dickinson University Dainel Eliades 14
Geometric attacks Removal attacks
Cryptographic attacks Protocol attacks
We considered Jpeg compression
Attacks
Fairleigh Dickinson University Dainel Eliades 15
Jpeg Compression
Jpeg (Joint Photographic Experts Group) uses a lossy compression technique which means that visual information is lost permanently.
Jpeg compression has four stages. Divides the image into 8x8 pixel blocks Calculates the Discrete Cosine Transform
(DCT) of each block A quantifier then rounds off the coefficients
according to the quantization matrix Final step is the binary encoder which
translates it to the data output stream.
Fairleigh Dickinson University Dainel Eliades 16
256 x 256 Imperceptibility Test
Original Image
Watermarked Image
Fairleigh Dickinson University Dainel Eliades 17
1024 x 1024 Imperceptibility Test
Original Image Watermarked Image
Fairleigh Dickinson University Dainel Eliades 18
256 x 256 Images
0
5
10
15
20
25
29.23% 38.46% 44.62% 56.92%
Jpeg Compression
To
tal N
um
ber
of
Pac
kets
Clock.tiffSeries2Airplane.tiffSeries4Chemical.tiffSeries6Walter02.tiffSeries8Walter04.tiffSeries10Walter06.tiffSeries12Walter08.tiffSeries14Walter10.tiffSeries16Walter12.tiffSeries18Walter14.tiffSeries20
Fairleigh Dickinson University Dainel Eliades 19
1024 x 1024 Images
0
50
100
150
200
250
300
350
400
34.73% 43.12% 48.49% 53.56% 58.34% 62.34%
Jpeg Compression
Nu
mb
er
of
Pa
ck
ets
AirportAirplaneMan
Fairleigh Dickinson University Dainel Eliades 20
A new Digital Rights Management System based on WASSFR was described.
Experimental results indicate robustness of the scheme to image processing distortions and attacks.
Results quantify trade-offs between information throughput and robustness.
Conclusions
Fairleigh Dickinson University Dainel Eliades 21
Digital Image ProcessingRafael C. Gonzalez, Richard E. Woods & Steven L. Eddins
Information Hiding–techniques for steganography and digital watermarkingStefan Katzenbeisser & Fabien A.P Petitcolas
USC-SIPI Image Databasehttp://sipi.usc.edu/database/
Jpeg Tutorial by Ray Wolfganghttp://dynamo.ecn.purdue.edu/~ace/jpeg-tut/jpegtut1.html
References