nyman 2004, new york city 1 e. ganic & ahmet m. eskicioglu a dft-based semi-blind multiple...

NYMAN 2004, New York City 1E. Ganic & Ahmet M. Eskicioglu

A DFT-BASED SEMI-BLIND MULTIPLE WATERMARKING

SCHEME FOR IMAGES

Emir Ganic and Ahmet M. EskiciogluDepartment of Computer and Information Science

Brooklyn College of the City University of New York2900 Bedford Avenue, Brooklyn, NY 11210


PROTECTION OF MULTIMEDIA DATAPROTECTION OF MULTIMEDIA DATA

Multimedia is the presentation of information in multiple forms of media (text, graphics, images, animation, audio, and video) in a given application.

Encryption and watermarking are two groups of complementary technologies for copy prevention and copyright protection.

A digital watermark is a pattern of bits inserted into a multimedia element such as an image, an audio or video file.

3 criteria to classify image watermarking systems Type of domain: pixel & transform Type of watermark: PRN sequence & visual watermark Type of information needed for detection: Original image,

secret keys & watermark Detection

False positives: detecting the watermark in an unmarked image

False negatives: not detecting the watermark in a marked image


DIGITAL WATERMARKINGDIGITAL WATERMARKING

Watermarking technology is becoming mature. Recent DWT or DCT domain watermarking schemes

Robust against a number of attacks Not useful for geometric attacks like rotation, translation, and

scaling Current focus is on DFT-based watermarking. In two papers, a circularly symmetric watermark is

embedded in the DFT domain Solachidis and Pitas [1999]: a 2D circularly symmetric

sequence in a ring covering the middle frequencies Licks and Jordan [2000]: use a watermark in the form of a

circle with a radius that corresponds to higher frequencies of the image

Recent work: Mehul and Priti [2003] embedding a watermark in low frequencies is robust to one

set of attacks embedding a watermark in high frequencies is robust to

another set of attacks


CIRCULAR WATERMARKCIRCULAR WATERMARK

We extend the multiple watermarking idea by inserting two circular watermarks in the DFT domain.

Test image: 256x256 Lena Two radii:

32 (corresponds to lower frequencies) 96 (corresponds to higher frequencies)

Attacks with MATLAB JPEG compression Gaussian noise Blurring Resizing Histogram equalization Contrast adjustment Gamma correction Scaling Rotation Cropping


TEST IMAGETEST IMAGE

Original Lena Watermarked Lena


ATTACKSATTACKS

JPEG Gaussian noise blurring Gamma correction

Resizing

Cropping

Histogram equalization Contrast adjustment Rotation

JPEG


DETECTIONDETECTION

Presence of the watermark is detected using the correlation

Decision rule H0: the image is watermarked with W if c T H1: the image is not watermarked with W if c < T

Threshold T = (0 + 1)/2 0: the expected values of the Gaussian probability density

functions (pdfs) associated with the hypotheses H0

1: the expected values of the Gaussian probability density functions (pdfs) associated with the hypotheses H1

N

u

N

vw vuMvuWc

1 1

* ),(),(


EXPERIMENTAL RESULTS:THRESHOLDS AND FALSE NEGATIVES

EXPERIMENTAL RESULTS:THRESHOLDS AND FALSE NEGATIVES

Radius = 96 Radius = 32

T % T %

JPEG 0.086 48 0.228 12

Gaussian noise 0.110 37 0.206 18

blurring 0.120 51 0.228 13

resizing 0.093 55 0.227 13

histogram equalization 0.272 1 0.267 14

contrast adjustment 0.273 0 0.232 11

gamma correction 0.271 0 0.231 11

scaling 0.251 1 0.233 11

rotation 0.142 35 0.174 42

cropping 0.154 21 0.150 34


EXPERIMENTAL RESULTS:THRESHOLDS AND FALSE POSITIVES

EXPERIMENTAL RESULTS:THRESHOLDS AND FALSE POSITIVES

Radius = 96 Radius = 32

T % T %

JPEG 0.086 40 0.228 7

Gaussian noise 0.110 24 0.206 13

blurring 0.120 41 0.228 8

resizing 0.093 45 0.227 8

histogram equalization 0.272 0 0.267 4

contrast adjustment 0.273 0 0.232 6

gamma correction 0.271 0 0.231 6

scaling 0.251 0 0.233 7

rotation 0.142 23 0.174 26

cropping 0.154 8 0.150 31


CONCLUSIONSCONCLUSIONS

Embedded in higher frequencies the percentage of false negatives or positives is higher for one

group of attacks JPEG, Gaussian noise, blurring, and resizing

the percentage of false negatives or positives is lower for another group of attacks

histogram equalization, contrast adjustment, gamma correction, scaling, rotation, and cropping

Embedding in lower frequencies the percentage of false negatives or positives is lower for one

group of attacks JPEG, Gaussian noise, blurring, and resizing

the percentage of false negatives or positives is higher for another group of attacks

histogram equalization, contrast adjustment, gamma correction, scaling, rotation, and cropping

For all attacks, the percentages of false positives are lower than false negatives.

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