Watermark

Wavelet Image Watermark robust against geometric transformations

AbstractTo solve the sensitive problem of signal processing and geometric distortion of digital image watermarking, an image watermarking algorithm against geometric attacks was proposed in the paper. After decomposing the whole image with 3 level of discrete wavelet transform and transforming the watermark image by Arnold shuffling, embed the watermark data to the media frequency coefficients of wavelet domain according to the conceal quality of Human Visual System (HVS); and extract two invariant centroids as factors to correcting geometric transformation by using the theories of invariant centroid, the watermarked image could be corrected. The experimental results show that the algorithm is robust to general signal processing and geometric attack such as rotation, scaling and translation.

Watermark Embedding Challenges

General digital watermark life-cycle phases with embedding-, attacking-, and detection and retrieval functions

SignalsS

Embedding Function E

Attacking Function A

Detecting Retrieval Function

ResultSecure Part In Secure Part In Secure Part

Arnold Scrambling of the Watermark Image

• The transformation for a square digital image is

Wavelet Transformation of a Carrier Image

Watermark Embedding Algorithm

(1) Use Haar wavelet, the images A be done 3 level discrete wavelet transform, to produce LL3, HL3, LH3, HH3 and so on ten sub-band.(2) Use ascending order for the intermediate region HL3, LH3 of image, get the sequence C, and note the location corresponding to order (3) Arnold scrambling the watermark information, then obtain scrambling watermark information W.(4) Using the multiplicative rule, large absolute value coefficient with C embed , then get the watermark information W.c i ′ = ci(1 + alpha*wi)where the size of determines the intensity of the image frequency modified by the watermark signal.

(5) According to corresponding sequence in step (2), the modified media frequency sequence c′i is assigned to corresponding location of original intermediate frequency regions HL3, LH3.

(6) Use the modified wavelet coefficients in step (5) by discrete inverse wavelet transform to get image embedded with the watermark information.

(7) Extract the two invariant centroid points tm, tn of the images embedded watermark information, and obtain the coordinates and corresponding radius r1, r2 of the two points as geometricdistortion correction key for watermark detection.

Watermark Detection Algorithm

(1) Use the methods described before as well as the key of geometric distortion of thewatermark image rotation, scaling, translation correction.

(2) Use DWT for watermarking image A ∗ with geometric distortion correction to get LL3, HL3,LH3, HH3 and so on ten sub-bands.

(3) According to the corresponding position sequence and the embedded watermarksequence size, a embedding position of intermediate frequency regions HL3, LH3 in watermarkimage is determined, and embedded watermark sequence c i ′ is obtained.

(4) Use the Eq. (4), to get scrambling watermark information W′.W′i = (c /ci − ′ 1)/alpha

(5) Use the saved Arnold scrambling key to do periodic transformation for W′, then get theextracted watermark image W∗.

Extraction of the Invariant Centroid and Parameter Correction of the

Geometric Distortion

• Extraction of the Invariant Centroid• Parameter Correction of Geometric Distortion• Image Rotation Correction Algorithm• Image Scaling Correction Algorithm• Image Translation Correction Algorithm

Wavelet Hiding strategy

Host Image Wavelet transform

LL3,LH3,HL3

Use LL3 but low energy or

LH3 and/or HL3 for higher

energy

Another strategy use only high value coefficients to hide your coefficients

Another strategy use additive way or multiplicative way

Watermark Algorithm

Host ImageWavelet

transformWavelet

transformWavelet

transform

LL3,LH3,HL3Use LL3 but low energy

Watermark Image

+*Wavelet inverse 3 levels

Watermarked Image

Arnold scrambling

Original image and its wavelet transform

Watermark and its wavelet transform

Watermarked Image

Scrambled and Descrambled Watermark

USE HL Band to Hide

Host ImageWavelet

transformWavelet

transformWavelet

transform

LL3,LH3,HL3Use HL3

Watermark Image

+*Wavelet inverse 3 levels

Watermarked Image

Arnold scrambling

Why 3 level wavelet transform

Because it is more robust to attacks

Image Rotation Attack with correctionin CH Band(HL)

ans = Correlation between watermark and recovered watermark 0.1215

RC4 could be used instead of Arnold

Host ImageWavelet

transformWavelet

transformWavelet

transform

LL3,LH3,HL3Use HL3

Watermark Image

+*Wavelet inverse 3 levels

Watermarked Image

RC4 EncryptionSecret Key

Other permutation methods can be used instead of Arnold

Host ImageWavelet

transformWavelet

transformWavelet

transform

LL3,LH3,HL3Use HL3

Watermark Image

+*Wavelet inverse 3 levels

Watermarked Image

Permutation

Encrypt Watermark using XOR

Host ImageWavelet

transformWavelet

transformWavelet

transform

LL3,LH3,HL3Use HL3

Watermark Image

+*Wavelet inverse 3 levels

Watermarked Image

XORSecret key

Increase the level of wavelet

Host Image Wavelet transform

Wavelet transform

Wavelet transform

LL4,LH4,HL4Use HL4 or LH4

or LL

Watermark Image

+*Wavelet inverse 3 levels

Watermarked Image

XORSecret key

Wavelet transform

Generate pseudo random signals for fingerprinting

Host ImageWavelet

transformWavelet

transformWavelet

transform

LL3,LH3,HL3Use HL3

+*Wavelet inverse 3 levels

Watermarked Image

Pseudo random

generator or LFSR

Hide Watermark inside another Watermark

Host ImageWavelet

transformWavelet

transformWavelet

transform

LL3,LH3,HL3Use HL3

+*Wavelet inverse 3 levels

Watermarked Image

Arnold Scrambling

Host Watermark

Watermark #2

Watermarked Watermark