NYMAN 2004, New York City 1 E. Ganic & Ahmet M. Eskicioglu A DFT-BASED SEMI-BLIND MULTIPLE WATERMARKING SCHEME FOR IMAGES Emir Ganic and Ahmet M. Eskicioglu Department of Computer and Information Science Brooklyn College of the City University of New York 2900 Bedford Avenue, Brooklyn, NY 11210

NYMAN 2004, New York City 2 E. Ganic & Ahmet M. Eskicioglu PROTECTION 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

NYMAN 2004, New York City 3 E. Ganic & Ahmet M. Eskicioglu DIGITAL 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

NYMAN 2004, New York City 4 E. Ganic & Ahmet M. Eskicioglu CIRCULAR 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

NYMAN 2004, New York City 5 E. Ganic & Ahmet M. Eskicioglu TEST IMAGE Original LenaWatermarked Lena

NYMAN 2004, New York City 6 E. Ganic & Ahmet M. Eskicioglu ATTACKS JPEG Gaussian noiseblurringGamma correction Resizing Cropping Histogram equalizationContrast adjustmentRotation JPEG

NYMAN 2004, New York City 7 E. Ganic & Ahmet M. Eskicioglu DETECTION  Presence of the watermark is detected using the correlation  Decision rule  H 0 : the image is watermarked with W if c  T  H 1 : 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 H 0  1 : the expected values of the Gaussian probability density functions (pdfs) associated with the hypotheses H 1

NYMAN 2004, New York City 8 E. Ganic & Ahmet M. Eskicioglu EXPERIMENTAL RESULTS: THRESHOLDS AND FALSE NEGATIVES Radius = 96Radius = 32 T%T% JPEG Gaussian noise blurring resizing histogram equalization contrast adjustment gamma correction scaling rotation cropping

NYMAN 2004, New York City 9 E. Ganic & Ahmet M. Eskicioglu EXPERIMENTAL RESULTS: THRESHOLDS AND FALSE POSITIVES Radius = 96Radius = 32 T%T% JPEG Gaussian noise blurring resizing histogram equalization contrast adjustment gamma correction scaling rotation cropping

NYMAN 2004, New York City 10 E. Ganic & Ahmet M. Eskicioglu CONCLUSIONS  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.