Watermarking for JPEG Image Using Error ...

Watermarking for JPEG Image Using Error Correction Coding Hailing Zhu, Willem A. Clarke and Hendrik C. Ferreira

Reed-Solomon (RS) code, Discrete Cosine Transform Abstract— Compression is the most common process that

(DCT), exclusive OR (XOR)

limits the robustness of watermarking. In this paper, we propose a watermarking method for JPEG compressed color images

in

the

semi-decompression

domain,

using

1. Introduction

Reed-Solomon (RS) codes. The watermark embedding and recovery processes can be applied without decompressing

With a proliferation of techniques for representation,

the compressed file completely. There is no perceptible

storage and distribution of digital multimedia information,

degradation between the watermarked image and the

the copyright protection issue such as unauthorized

original image. Experimental results show that the scheme is

copying, distribution and manipulation, is a growing

robust against some distortion attacks and JPEG lossy

concern. The prevention of digital data duplication

compression with different compression rates.

sparked the digital watermarking research techniques.

Index Terms— watermarking, JPEG, spread spectrum communication,

Error

Correction

Code

(ECC),

Digital Watermarking is a method of embedding some information into image, audio or video in a statistical and perceptually undetectable way. Watermarking techniques can at least ensure that the ownership information is embedded into the image, thus preventing or deterring

Manuscript received March 9, 2004. This work was

users from illegal usage. In addition to copyright

supported by the NRF under grant number 2053408.

protection, digital watermarking has other features, such

Hailing Zhu is with the Department of Electrical and Electronic Engineering, Rand Afrikaans University, P.O. Box 524, Auckland Park, 2006,

South

Africa

(phone:

+27-11-489-2463/2107;

fax:

+27-11-489-2357; e-mail: hlz @ ing.rau.ac.za).

Engineering, Rand Afrikaans University, P.O. Box 524, Auckland Park, South

Africa

(phone:

+27-11-489-2463/2107;

fax:

+27-11-489-2357; e-mail: wacl @ ing.rau.ac.za).

Hendrik C. Ferreira is with the Department of Electrical and Electronic Engineering, Rand Afrikaans University, P.O. Box 524, Auckland Park, 2006, South Africa (phone: +27-11-489-2463/2107; fax: +27-11-489-2357; e-mail: hcf @ ing.rau.ac.za).

control. It may also provide a mechanism for embedding descriptive or reference information into a given signal. In this work we focus on the application of copyright

Willem A. Clarke is with the Department of Electrical and Electronic

2006,

as content-based authentication and playback/copy

protection. For the purpose of ownership identification, a robust invisible watermark, which must be identified from the host data even with malicious manipulation, is required. A variety of watermarking schemes have been reported in recent years. Most of them are based on ideas known from spread spectrum communication. In practice, spread spectrum watermarks in their most simple form are vulnerable to a variety of attacks and modifications. To

improve the robustness of the spread spectrum watermarking, several methods have been proposed,

RGB color space is highly correlated and is not suitable

exploiting results and concepts from digital

for watermarking applications, except for the blue channel,

communication theory. For instance, in [5], ECC

used by some researchers because of its low sensitivity to

techniques, such as binary BCH and convolutional codes,

human perception [7]. For the application of

are used advantageously for watermarking. In [6], the

watermarking, the potential of these three channels can be

authors show that the (15,7)-RS code is the most

exploited by transforming colorspace to decrease the

convincing error correction code. Most of this research is

correlation among them. In [3], the authors compare

based on the grayscale raw image.

various color models, such as HIS, L*a*b, YIQ, YUV, and show the superiority of linear and uncorrelated

Multimedia data is usually compressed using standards

transforms YUV. In YUV color space, there are

such as JPEG, MPEG. Compression is the most common

luminance (Y) and chrominance (U and V) components.

process that limits the robustness of watermarking. In [2],

The three components have little statistical correlation. In

a spread spectrum technique is used to embed the

this paper the luminance and chrominance band of YUV

watermark, but the noise like watermark may be

color space is used to embed watermark.

suppressed significantly by JPEG compression. In [1,4], the authors described the basic spread spectrum

This paper is organized into four sections. The next

watermarking of compressed images. Because of the

section introduces the proposed watermarking method,

sensitivity of the DC coefficients, the watermark strength

followed by simulation results and conclusion in Section 3

(amplitude factor) is limited to the cover image. Thus the

and 4 respectively.

performance of the watermarking scheme is affected.

2. Watermarking Embedding and Retrieval In this paper we describe a watermarking scheme, that modifies DC coefficient of the luminance and

Basically one bit of the watermark information is

chrominance components of the JPEG color image, based

embedded in an 8-by-8 block by modifying its quantized

on spread spectrum communication. The property of the

luminance and chrominance DC coefficients slightly.

DCT coefficients between different JPEG compression

Changes in the quantized DC coefficients are visually

ratios is exploited for watermark detection. The extraction

detected. However, a small change on the last bit in the

processes utilize the compressed bitstream to reconstruct

DC coefficients can be perceptually undetectable. Figure

the pre-quantized DCT coefficients without

1(a) shows how to embed one bit of watermark

decompressing the image into pixel domain.

information into the quantized DC coefficient of an 8*8 block using the XOR function. The watermark bits are

There are some appropriate modifications on the embedding and extraction process in spread spectrum

interrelated with the cover image, and the watermark bits can be calculated directly from watermarked image.

watermarking to adapt to the sensitivity of the DC coefficients. To improve the performance of

Quantization is defined as the division of each DCT

watermarking, we use Error Correction Coding (ECC) to

coefficient by its corresponding quantizer step size,

deal with burst errors that occur in the watermarked

followed by rounding to the nearest integer. So we get

image. In this watermarking scheme Reed-Solomon coding is introduced. In our watermarking scheme, the (15, 7)-Reed-Solomon code was found by experiments to be the best error correction code.

Fmp =

FP × Q Qm

(1)

In Eq.1, Fp is a DCT coefficient vector of an arbitrary 8*8 RGB color transformations

block, Q is the quantization table for the present JPEG

lossy compression, Qm is the pre-quantization table, and F

m

p

I. 3. EXPERIMENTS AND RESULTS

is pre-quantized coefficient. If we quantize a DCT

coefficient with a reference quality factor, then this

In our simulation, the 512*512 image “Lion”(Figure 2a)

pre-quantized coefficient can be reconstructed after

is compressed with a pre-reference quality factor of 50. A

subsequent JPEG compression.

108-bit random sequence is used as watermark. The watermark information bits are encoded with different

In general, JPEG recommends a quality factor of 50-75

Reed-Solomon codes, i.e. RS (15,7), RS (15,9), RS

for merely acceptable quality. The default quality factor

(15,11), RS (31,7), RS (31,11), and RS (31,19). The

for JPEG compression is 50. In our scheme, the

encoded watermark bits are embedded using the method

quantization tables Q50 is set as the reference quantization

described in section 2.

table when the watermark information is embedded. Using Eq.1 the pre-quantized coefficient can be reconstructed after subsequent JPEG compression.

The Peak Signal to Noise Ratio (PSNR) is used to evaluate the distortion of watermarked images. The corresponding PSNR values are provided in Figure 3. To

For spread spectrum watermarking, in the absence of the

compare and evaluate the error correction capabilities of

original image (blind watermarking), matched bandpass

the various Reed-Solomon codes, the watermarked image

filtering is applied before correlation to decrease the

is compressed with a variety of quality factors. Figure 3

contribution of the original image to the correlation in

shows the different influence of these Reed-Solomon

watermark detection [4]. To perform bandpass filtering

codes on proposed watermarking method after

the JPEG image has to be decompressed completely. In

compressing the watermarked image with a variety of

our method, the watermark bits are calculated directly

JPEG compression rates. We can see that there is no error

from the watermarked image. Since the quantized DC

when the JPEG quality factor is above 30. Moreover, the

coefficients and quantization tables can be easily

(15,7)-Reed-Solomon code has the best error correction

extracted from the JPEG bits stream, the pre-quantized

capability in proposed watermarking method. Using a

coefficient can be reconstructed easily after future JPEG

(15,7)-Reed-Solomon code, we found that for a JPEG

compression. Figure1 (b) shows how to extract one

quality factor larger than 20 there are no errors.

watermark bit from reconstructed DC coefficient. With the XOR function, there is no need to perform filtering

The classical test image 512*512 “Baboon” (figure 2b)

and the watermark extraction is performed at the

from StirMark homepage was watermarked using the

semi-decompressed stage.

proposed watermarking method with a

Furthermore, to improve the accuracy of the watermark

(15,7)-Reed-Solomon code. The watermark is a binary

extraction and the ability to defend against attacks, ECC is

image of size 9*12. To evaluate the robustness against

used to deal with random and burst errors, which occur in

malicious modifications, we manipulated the

the watermarked image. The ECC is used for the

watermarked image using Photoshop. A flower from other

watermark sequence. Due to its burst error correction

image was pasted and the nose of baboon was modified.

property, Reed-Solomon code is adopted in our scheme.

The Normalize Correlation (NC) is used to measure the

In order to alleviate the load on the Reed-Solomon (RS)

quantitative similarity between the original watermark and

code, block interleaving is applied.

the extracted watermark. Figures 4a-b shows the original image and the watermarked image with manipulation. The

According to spread spectrum communications, a

PSNR value of the watermarked image is 31.3797dB. The

Pseudo-random Noise (PN) sequence is used to

original watermark and the watermark extracted from

randomize the watermark bits. The key, which generates

Figure 4b are shown in Figure 4c, the NC value is 1.

the PN sequence, is needed to the watermark extraction.

Figures 4d-f show the extracted watermarks and the corresponding NC values that come from the “corrupted”

watermarked image (Figure 4c) undergoing lossy

[7] A. Nikolaidis, F. Jordan and F. Bossen, “Digital signature of Color

compression with different JPEG compression rates. We

images Using Amplitude Modulation”, Proc. SPIE Electronic Imaging

can see when the quality factor is above 40 the watermark

97, Storage and Retrieval for Image and Video Databases, pp.518-526,

can be extracted exactly.

San Jose, CA, Feb. 1997 [8] Scott Craver, Nasir Memon, and Boon-Lock Yeo. “Resolving

4. Conclusion

rightful ownerships with invisible watermarking techniques:

In this paper, we presented a digital watermarking method that is robust to lossy compression and malicious modifications for JPEG color image. Using the XOR function, the watermark can be retrieved exactly without the original image. The watermark embedding and retrieval processes are preformed without decompressing the JPEG image completely. In conjunction with the error correction capability of Reed-Solomon codes, the watermarking is robust against recompression processes and some image processing.

II. REFERENCES

[1] Pei-chun Chen, Yung-sheng Chen and Wen-hsing Hsu “Adaptive-rate image watermarking based on spread spectrum communication technique”, 3rd World Multiconference on Circuits, Systems, Communications and Computers (CSCC'99), Athens, Greece, July 1999. [2] I.Cox, J.Kilian, F.Thomoson Leigton and T.Shamoon, “Secure Spread Spectrum watermarking for Multimedia”, IEEE Trans. On Image Processing, vol.6, NO. 12, DEC.1997 [3] S.A.M. Gilani, I. Kostopoulos and A.N. Skodras, “Color image-adaptive watermarking”, Proc. 14th Int. Conf. on Digital Signal Processing (DSP2002), Vol. 2, pp. 721-724, Santorini, Greece, 1-3 July 2002 [4]Frank Hartung and Bernd Girod “Watermrking of uncompressed and compressed video”. Signal Processing Vol. 66, No. 3, May 1998 pp.283-301. [5] J.Hernàndez, J.-F. Felaigle and B. Macq, “Improving Data Hiding by Using Convolutional Codes and Soft-Decision Decoding”, Proc. of the SPIE/IST: Security and Watermarking of Multimedia Content, San Jose, USA, pp.24-47, Jan.2000 [6] N. Terzijia, M. Repges, K. Luck, W. Grisselhardt, “Impact of different Reed-Solomon codes on digital watermarks based on DWT”, Multimedia and Security Workshop at ACM Multimedia 2002

Limitations, Attacks, and Implications”. IEEE Journal on Selected Areas in Communications, Vol.16. May 1998

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R S 1 5 , 9 P S N R = 2 9 .5 2 1 2

R S 1 5 ,1 1 P S N R = 2 9 . 6 4 7 5

R S 3 1 ,7 P S N R = 2 9 .5 8 9 5

R S 3 1 , 1 1 P S N R = 2 9 .5 9 7 4

R S 3 1 ,1 9 P S N R = 2 9 . 5 7 2 7

6

6 0 .0 0 %

5 0 .0 0 %

Errors

4 0 .0 0 %

3 0 .0 0 %

2 0 .0 0 %

1 0 .0 0 %

0 .0 0 % Q F=50

Q F=40

Q F=30

Q F=20

J P E G C o m p r e s s io n

Q F=15

Fig. 3. Performance of various RS-codes after suffering JPEG compression with different quality factor and their corresponding PSNR

(a) Original baboon image

(b) Watermarked image with modification

(c) Original watermark and recovered watermark

(d) Quality Factor =40 NC=1

(e) Quality Factor =30 NC=0.9130

(f) Quality Factor=25 NC=0.8997

Fig. 4. Modification and compression attacks