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Digital watermarking:

algorithms and applications

Park, Jungjin

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Index

Watermarking embedding

Watermarking detection

Document Graphic

Audio

Video

Image

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Watermark embedding

Watermark embedding scheme

embed the watermark directly into the host data or to a transformed version

of the host data

(DCT, wavelet)-popular due to the natural framework for incorporating

perceptual knowledge into the embedding algorithm

-Many of compression techniques such as JPEG work in the same framework

and this allows for watermarking of the compressed bit stream with only

partial decoding

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Watermark embedding

S: original host signal (image luminance values or DCT coefficients)M: watermark message (serial number or credit card number logo)

K: secret key

WSX

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Watermark embedding

Secret key is used to generate a random sequence to embed in the host

signal

It is also used to determine a random sequence which identifies locations in

the host signal for watermarking embedding

-without knowledge of the key, it should be difficult to remove or alter theembedded message without destroying the original content

no-key or public-key (QIM) may be desirable .

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Watermark detection

Detection or verification: the process of making a binary decision at the

decoder, it check whether a specific watermark

is or not present in the received data

Type I (false positive) : the case where a watermark is detected when it

does not existType 2 (false negative) : the case when a existing watermark is not

detected

Identification: the process of being able to decode one of N possible

choices at the receiver.

Open set : the possibility that one of N or no watermark exists in the data

Closed set : the problems where one of N possible watermarks is known to

be in the received data and the detector has to pick the most likely one

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Watermark detection

Blind detection

S is not available at the decoder,

S acts as an additive noise component in the watermarking detection process

S is available at the decoderIt could be used to estimate the channel distortions and invert them to

provide better detection performance

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Watermark detection

WW

WWEE

WW

SW

Typical watermarking detector

Watermark detection is performed by comparing the correlation coefficient

to a threshold value which can be modified according to the tradeoff

between probability of detection and the probability of false alarm

pWW

pWW

TT

Watermark W detected

Watermark W is not detected

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Documents watermarking

Document watermarking can be achieved by altering the text formatting or by altering

certain characteristics of textual elements

Line- Shift Coding

The most easily discernible by readers

The most robust type of encoding in the presence of noisethe long lengths of text lines provide a relatively easily detectable feature

Altering a document by vertically shifting the locations of text lines

decoding without need of the original image

Original image is known to have uniform line spacing

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Word-Shift Coding

Altering a document by horizontally shifting the locations of words within

text lines

The spacing between adjacent words on a line is often varied to support textjustification.

less discernible to the reader than line-shifting

Decoding need the original image

variable spacing

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Feature coding

Chosen text features are altered by extending or shorting the lengths by one

or more pixels

Decoding require the original image

Ex) vertical end line top of letters, b,d,h,etc

Altered by expending or shorting lengths

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Graphics watermarking

Watermarking of facial animation parameters (FAP) defined by the

MPEG-4 standard

66 FAPs

global head motion parameters

- Head pitch and yaw angles

local face motion parameters

-opening of eyelids , opening of lips, movement of innerlip corners

16 FAPs (jaw, chin, inner lips and cornerlips)

12 FAPs (eyeballs pupils eyelids), 8 FAPs eyebrows ,

4 FAPs cheeks , 5 FAPs tongue , 3 FAPs global head rotation,

10 FAPS outer lip position, 4 FAPs nose, 4 FAPs ears

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)](),()/,/([)()( ktkPNNtMkWMtFAPtFAP kWM

k

Embedding

One bit of watermark information is embedded in a block of facial

animation parameters (FAPs) -using PN sequence

generated by any random number generator that produces binary output

values -1 and +1)

Minimize visible distortion

-apply an amplitude adaptation

Limit the maximum deviation of the watermarked FAPs from the

unwatermarked FAPs to 3% of dynamic range for local FAPs like lip

movement, and 1% of the dynamic range for global FAPs like head

rotation.

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),())()((),(

1)1( 1)1(

tkPNtFAPtFAPsignnmWM

Mm

Mmk

k

Nn

Nnt

WM

k

Detection

Extracted from the watermarked parameters directly by

Subtraction of the unwatermarked FAPs from the watermarked FAPs

Subsequent correlation with the same filtered PN sequence that has been used

for embedding

Thresholding as a bit decision

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Video watermarking

Current issue

Design of an effective copy control system for DVD include s the

placement of the detector

Two proposals for detector placement

Watermark detection in the drive

Advantage : Pirated content cannot leave the drive in playback mode

or recording mode

Watermark detection within the application

Advantage : ability to provide a more complex detector and

flexibility of extending the scheme to other data type

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Video watermarking

Unique requirement for DVD application

Copy generation management

Ability to detect the copy once state and change it to copy no more state after

the recording

Two approach

Secondary watermarks, Ticket

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Video watermarking

Scene-adaptive video watermarking technique

based on temporal wavelet transform

using a tow-band perfect reconstruction filter bank

Separates static areas from dynamic areas so that separate watermarkingstrategies can be applied to the different areas.

constant watermarking apply for static, varying watermark apply for the

dynamic areas to defeat watermark deletion through frame averaging

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Video watermarking

Real time watermark embedding of compressed video

adding the watermark by modifying the fixed length and variable length

codes in the compressed video bit stream

allow for a computationally efficient way of real-time watermark insertion

allow for a relatively high payload

drawback: decoding the bit stream removes the watermark

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Video watermarking

More robust technique for real time watermark embedding

adding the watermark by enforcing energy differences between various

video regions

This technique is done by discarding high frequency components

only partial decoding of a compressed video bit stream is necessary to

apply this watermark

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Audio watermarking

Audio watermarking requirements

Inaudible

Robust :filtering, resampling, compression, noise, cropping, A/D-D/A

conversion

Embedded directly in the data

self-clocking for ease of detection in the presence of cropping and time-

scale change operations

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Audio watermarking

Phase coding

Work by substituting the phase

of an initial audio segment with

a reference phase that

represents the data

For the decodingprocess

The synchronization of the

sequence is done before

decoding

The length of the segment and

the data interval must be

known at the receiver

The value of the phase of segment is detected as a binary string

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Audio watermarking

Spread spectrum

Direct Sequence Spread Spectrum

encoding(DSSS)

spreads the signal by multiplying it by a chip(key),

a maximal length pseudorandom sequence- applied tothe coded information to modulate the sequence into

a spread spectrum sequence

The spectrum of the data is spread over the

available band

the spread data sequence is attenuated and added tothe original file as additive random noise

decoderpseudorandom key(chip) is needed to decode

signal synchronization is done

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Audio watermarking

Unlike phase coding, DSSS introduced additive random noise to the

sound

to keep the noise level low, inaudible

The spread code is attenuated to roughly 0.5 percent of the dynamic

range of the host sound file

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Audio watermarking

Echo data hiding

Embedding data into a host audio signal by

introducing an echo

-data are hidden by varying three parameters of

the echo

Initial amplitude, offset, decay rate

Zero represent a binary zero ,one represent a binary one < threshold (human ear can

resolve the echo)

It is possible to encode and decode information in the form of binary digits into amedia stream with minimal alteration to the original signal

to minimize alteration

Addition of resonance simply gives the signal a slightly richer sound

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Image watermarking

Texture block coding Detection

1. Autocorrelate the image with itself. This will produce peaks at every point

in the autocorrelation where identical regions of the image overlap.

2. Shift the image as indicated by the peaks in Step 1.

Now subtract the image from its shifted copy

3. Square the result and threshold it to recover only those values quite close to

zero. The copied region will be visible as these values.

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Image watermarking

Transform domain watermarking

robust to common compression techniques

block-based DCT which is the fundamental building block of current image

coding standard JPEG and MPEG

a pseudorandom subset of the blocks are chosen and a triplet of midrange

frequencies are altered to encode a binary sequence

Watermarks inserted in the high frequencies are vulnerable to attack

The low frequency components are perceptually significant and sensitive toalterations

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Image watermarking

two watermarking techniques based on visual models

Image-adaptive DCT approach

Image-adaptive DWT approach

Utilizing visual models which have been developed in the context of image

compression

Very effective visual models have been developed for compression

applications that take into account frequency sensitivity, local luminance

sensitivity, contrast masking

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Image watermarking

otherwiseX

tXifwtXX

bvu

C

bvubvubvu

C

bvubvu

bvu ,

,

,,

,,,,,,,,,,*

,,

bvuX ,, DCT coefficient

Watermarked DCT coefficients

Sequence of watermark values

Computed JND from the visual model

bvuw ,,

C

bvut ,,

*

,, bvuX

IA-DCT

embedding

The watermark is only inserted into the luminance component of the image

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Image watermarking

ectednotiswwatermarkT

ectedwwatermarkT

EE

ww

t

ww

XXw

ww

ww

ww

ww

C

bvu

bvus

bvu

bvubvubvus

det

det

*

*

*

*

*

,,

*,,,*

,,

*

,,,,

*

,,,

Detection

Normalized correlation detection scheme based on classical detection for the

IA-DCT scheme

Received watermark

Normalized correlation coefficient between two

signals

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Image watermarking

otherwiseX

tXifwtXX

flvu

F

flflvuflvu

F

flflvu

flvu,

,

,,,

,,,,,,,,,,,*

,,,

flvuX ,,,

flvuw ,,,

*

,,, flvuX

F

flt ,

IA W embedding

Wavelet coefficient at position (u,v) in resolution level l, frequency

orientation f

Watermarked wavelet coefficient

Computed frequency weight at level l and frequency orientation f

Watermark sequence

watermark is inserted only in the luminance component of the image

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Image watermarking

flfl ww

flfl

ww

F

fl

flvus

flvus

flvuflvuflvus

EE

wwfl

t

w

w

XXw

,,

*

,

*

,

,

*

,,,,*

,,,,

*

,,,,,,

*

,,,,

),(

)}(),({max

1

1

***

**

**

,

*

1),(

1),(

fl

N

N

wwwwflww

N

lflww

lww

N

fflww

fww

f

f

IA W detection

Correlation is performed separately

IA-W scheme is based on a much simpler visual model which only takes into

account frequency sensitivity, the multi resolution structure of the watermark

and the watermark detection scheme results in a very robust scheme

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Image watermarking

Digital watermarking by geometric warping

Embeds information in an image by changing the geometric features of the image

the watermark is formed by a predefined dense pixel pattern, such as a

collection of lines

Salient points in an image are warped into the vicinity of the line pattern in

such a way that the changes to the image are imperceptible

subdivide the image in a number of blocks. Find a fixed number of most

significant pixels, these are called salient points

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Image watermarking

Detection

Determining whether a significantly large number of points are within the

vicinity of the line patterns

Advantage

detection is computationally fasterEasier to detect the watermark in images have been rotated, scaled, or

distorted by a geometric transformation

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Questions?