A NOVEL COPYRIGHT PROTECTION FOR DIGITAL IMAGES

USING EXTRA SCRAMBLED INFORMATION

Jin-Wook Shin, Jucheng Yang, Dong-Sun Park

Dept. of Infor. & Comm. Eng., Chonbuk Nat'l University, Jeonju, Jeonbuk, 561-756, Korea

Sook Yoon

Dept. of EECS, University of California at Berkeley Berkeley, CA 94720

Keywords: Digital content, Copyright protection, Extra scrambled information, Watermarking, Fingerprinting.

Abstract: Both watermarking and fingerprinting techniques can be used for protecting digital contents with

different properties. A watermarking system may degrade the fidelity of the digital contents by

embedding watermark messages, while a fingerprinting system may have high computational

complexity to generate unique features for digital contents. In this paper, we propose a novel

technique can distribute digital images without embedding messages related with them, and save extra

scrambled information on simple fingerprints stored in a certified database. Experimental results show

that the proposed method outperforms an existing method for various signal processing attacks. The

proposed technique is also flexible and fast so that it can be used for real-time applications.

1 INTRODUCTION

The explosive growth in Internet and its supporting

digital technology for the last decade brings the

production and spread of huge amount of

multimedia data. Since it is very easy to copy, edit,

save and/or transmit digital data, illegal operations

on digital data, such as illegal copy and distribution,

have been frequently conducted without having any

charges against those actions. Protection of

intellectual property rights, therefore, is one of the

major issues in the current Internet era.

Cryptography (Cox, 2002) can be used to protect

digital data during transmission through digital

networks from network eavesdroppers, but it is not

appropriate for cases of illegal copy and

distributions. Recently, digital watermarking

techniques are focused as the copyright protection

technique for those cases. Using this technique, we

can embed information of manufacturers or

authorized users inside the digital contents to

prevent the illegal actions. The basic requirement of

a watermarking technique is to minimize the

degradation of the original contents when

embedding a watermark message and the watermark

itself should be unperceivable to other users.

Depending on different applications, a watermarking

system should have required properties including

fidelity, robustness against various signal processing

attacks, computational complexity and cost.

Various researches have been performed on

developing efficient watermarking systems (Huang,

2004) (Schydel, 1994). Most watermarking systems

developed so far one of two types depending on the

method of embedding watermark messages : spatial

domain and frequency domain methods.

Since watermarking techniques embed

watermark messages in the digital contents, slight

degradation of quality cannot be avoided. If a digital

contents experience many signal processing

operations during transmission and distribution, the

embedded watermark message may be severely

affected and hard to recover.

A fingerprinting technique (ISO/IEC 21000-11,

2004), included in MPEG21 part11, extracts unique

features from digital contents using computer vision

techniques, saves them in a database, and uses them

when there is a need to prove the identification of

the digital contents. Since this method distributes the

Shin J., Yang J., Park D. and Yoon S. (2006).

A NOVEL COPYRIGHT PROTECTION FOR DIGITAL IMAGES USING EXTRA SCRAMBLED INFORMATION.

In Proceedings of the First International Conference on Computer Vision Theory and Applications, pages 27-32

DOI: 10.5220/0001367100270032

 SciTePress

original contents without modifying any values, it

may endure more changes during distribution.

However, this technique is usually not flexible

because it cannot embed external information.

Moreover, it is usually time-consuming due to the

high computational complexity implementing

computer vision techniques.

In this paper, we propose a novel copyright

protection technique for digital images using

positive features of both watermarking and

fingerprinting techniques. The proposed method

uses external copyright messages and original digital

contents to generate extra scrambled information.

Random number generator is used to randomly

select the elements of digital contents. The generated

extra scrambled information contains the

information of both external copyright messages and

original digital contents. The generated information

can then be stored in a certified database with initial

seeds for random number generator. The original

digital contents can be distributed without having

any changes in element values. If there is a need to

identify either the external copyright message or the

original contents, the stored extra scrambled

information can be used for identification. The

proposed technique generates and saves extra

scrambled information as a function of external

distributes the original contents. Therefore, there is

no degradation in fidelity on the distributed contents.

In addition, in generating the extra scrambled

information we use a simple and fast spatial domain

insertion method so that the proposed technique has

a very low computational complexity.

This paper is organized as follows. In section 2,

related techniques including watermarking and

fingerprinting models briefly described. The

proposed technique is explained in detail in Section

3. Experimental results and conclusion are described

in Section 4, 5, respectively.

2 RELATED WORKS

2.1 Watermarking

In typical watermarking systems, a watermark

message which contains information on

manufacturers or authorized users is embedded in

the digital contents and distributed to the outside

world. The embedded watermark message should

not be perceivable not to degrade the quality of the

digital contents. The embedded watermark message

can be extracted to resolve legal disputes on the

digital contents such as illegal copy, modification

and distribution.

Fig. 1 shows the conceptual block diagram of a

typical watermarking system. It consists of a

embedder and a detector. The embedder embeds the

watermark message to the original content and the

watermarked contents are distributed. The

watermarked contents can be modified by various

signal processing operations or malicious attacks.

The watermark detector is to detect a watermark

message form the corrupted version of the digital

contents. Various techniques have been developed

for the better performance depending on the specific

applications (Nikolaidis, 2001) (Fazam, 2001).

Figure 1 : General watermarking system.

The properties required for a watermarking

system can be varied according to the applications.

Some properties including fidelity, robustness,

computational complexity, and informed/blind

detection can be found in (Cox, 2002).

2.2 Fingerprinting

A fingerprinting technique (ISO/IEC 21000-11,

2004) is can be also used to protect digital contents

from illegal uses as in the watermarking system. The

main difference between two methods in that a

fingerprinting system extracts features from digital

contents and uses the features for identifying the

digital contents while a watermarking system

embeds an external watermark message in the digital

contents. Therefore, this fingerprinting technique

does not embed any information on the digital

contents.

The conceptual block diagram of a fingerprinting

system is shown in Fig. 2. It consists of two

fingerprint generators and a comparison part. The

technique usually employs computer vision

techniques to generate an invariant fingerprint from

the digital contents.

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Figure 2: Fingerprinting system.

The generated fingerprint is stored in a database

and then it can be used for comparison whenever a

legal dispute happens. As in the figure, the

fingerprinting technique does not embed any

information in the digital contents. The digital

contents is not modified and distributed to outside so

that there can be no degradation in the contents.

Since this technique usually uses time-consuming

technique to find unique fingerprint, it is very hard

to apply them to real time applications.

3 PROPOSED METHOD

The method proposed in this paper combines the

features of watermarking and fingerprinting. The

method extracts some simple information such as

intensity value from original digital contents and

distributes the original contents as in the

fingerprinting technique. In the meanwhile, it also

generates extra scrambled information with external

from the contents.

Fig. 3 shows the block diagram of the method. In

the figure, original digital contents are used to

generate extra scrambled information as a function

of external copyright message and random number

sequences. The resulting extra scrambled

information and additional parameters of the

generator may be stored in a certified database for

later identification purposes. The original contents

may then be distributed without changing any

temporal or spectral information. The stored

information can be used whenever there is a need to

prove the identification of the digital contents or the

existence of the copyright message in the stored

information. The detection process uses the

information stored in the database and the same

procedure to generate the extra scrambled

information for the copyright message. In this

method, we used a pseudorandom number generator

and a spatial domain to generate to extra scrambled

information.

3.1 Extra Scrambled Information

Extra scrambled information is a binary data that

combines the information from the external

represents the copyright message or the original

work depending on applications. In other words, it

can be used to identify the copyright message or the

original digital contents itself.

The extra scrambled information generator can

be depicted as in Fig. 4. It consists of a position

selection part using three random sequences from

the random number generator, and a binary data

generator part to combine information from the

previous part. In the figure, for simplicity, we used a

still image as the original digital contents. In this

system, it is defined that original image is X, random

sequence value K, and copyright message W.

Figure 3: Proposed block diagram.

A NOVEL COPYRIGHT PROTECTION FOR DIGITAL IMAGES USING EXTRA SCRAMBLED INFORMATION

Figure 4: Generation of extra scrambled information.

The elements of original image, X(X

, X

), are

N-bit gray values and the elements of copyright

message, W(W

, W

), are assumed to be binary

image. Three random number sequences are

generated using initial seeds. Two are used to select

position of pixels in the input image and the last one

is used as a temporary gray value.

The pixel position selector receives two random

sequences as the coordinates of a pixel and outputs

the pixel pointed by these coordinates. The binary

data generator receives the pixels from the pixel

position selector, and the temporary gray sequences,

from the random sequence generator. Using these

values, it computes temporary binary image T as in

the Eq. 1.

⎭

⎬

⎫

⎩

⎨

⎧

⎩

⎨

⎧

−=

≥

== 1,...,1,0

),(0

),(1

gyxXif

kkk

(1)

In the equation, 0 ≤

g ≤ 2

–1, k = W

× W

Finally, the temporary binary image T is

exclusive-ORed with a binary copyright image to

generate extra scrambled information(ESI) as in Eq.

ESI (x,y) = W(x,y)

⊕

T(x,y) (2) (2)

The generated binary extra scrambled

information, ESI, is stored in a certified database

with the random number seed values for later

extracting the copyright image.

3.2 Extraction of Copyright Message

A digital contents received from Internet can be

degraded by noise or malicious attacks. Due to the

degradation of digital contents, a copyright message

embedded in extra scrambled information can also

be affected. Fig. 5 shows the extraction process.

Figure 5: Extraction of copyright message.

The method is very similar to the extra

scrambled information generator process. It

generates two random numbers using the initial

seeds from the database and uses the sequences to

select positions of pixels in the input image. It also

uses one random sequence as temporary gray values

to calculate a temporary binary image as in Eq. 1.

Using the temporary binary image and extra

scrambled information from database, we can

compute the received external copyright message W’

as in Eq. 3.

W’ = ESI(x,y)

⊕

T(x,y) (3)

In this equation, the received image is X’,

temporary image, T’, and extracted copyright

message, W’.

4 EXPERIMENTAL RESULTS

Performance measures in watermarking or

fingerprinting systems can be varied dependently on

the types of applications. To evaluate the

performance of the proposed method, we used a

popular benchmark test called Stirmark (Nikolaidis,

2004) (Website). This algorithm generates various

spatial signal processing images such as rotation,

cropping, median filter, adding noise, and etc. Bit

Correct Ratio (BCR) is mostly used in this paper to

show the correctness of the extracted copyright

message and it is defined in Eq. 4 (Chang, 2004).

%100

WX W

⎟

⎠

⎞

⎜

⎝

⎛

⊕

−=

∑∑

jiji

BCR

(4)

In this equation, w and w’ are the original

watermark and the extracted watermark at the

detector side, respectively and ⊕ denotes the EX-OR

operator.

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In the experiment, we used the 512×512 Lena

image with 8-bit gray scale as the original digital

content and a 64 × 64 binary image as the copyright

message. Total attacked 108 images generated using

Stirmark algorithm are used to verify the proposed

method. Fig. 6 shows the original Lena, binary

information, respectively.

(a) Original Lena

(b) Copyright message (c) Extra scrambled information.

Figure 6: Extraction of copyright message.

After degrading the original contents with some

signal processing attacks such as histogram

equalization, median filtering and scaling, we

evaluate the performance using the BCR. Fig. 7

shows the results extracted copyright message with

BCRs. For these typical attacks, it still shows very

high BCR under those attacks.

(a) Histogram equ. : 90.6% (b) Median(3×3) : 93.7%

(e) Noise(20%) : 75.4% (f) Scaling(90%) : 94.2%

Figure 7: Extracting results.

The performance of the proposed method is

compared to one of the leading research results as in

Table 1. C. Chang (Chang, 2004) proposed a

wavelet transform-based watermarking system using

artificial neural networks. As seen in the table, the

proposed method shows much higher BCR

comparing to the method in the reference.

Table 1: The comparison of BCR under various attacks.

Attack Types

Proposed

Method

C. Chang

Histogram Equ. 90.67% -

Median Filter 93.7% 89.25%

JPEG 94.5% 88.43%

Scaling 94.8% 78.58%

We summarize several properties of the propose

method as follows:

① Fidelity : Embedding a watermark message to

other watermark system requires the modification of

pixel values in the spatial domain or frequency

components in the frequency domain. This degrades

the fidelity of the digital contents. On the contrary,

the proposed method is not directly change the

original contents as in the fingerprinting technique,

so that it keeps the fidelity to 100%.

② Required space : The proposed method

requires to have a space to store a binary scrambled

information in a certified database. The extra

scrambled information has the same size of the

A NOVEL COPYRIGHT PROTECTION FOR DIGITAL IMAGES USING EXTRA SCRAMBLED INFORMATION

③ Computational complexity : The

computations in the proposed method are the

magnitude comparison and the exclusive-OR

operation. The processing time for these operations

is less than 10 ㎳ and should be very short so that

the method can be used to a real time application

④ Robustness : Most watermarking systems

require to have robustness against various signal

processing attacks. Various experiments are

performed to evaluate the proposed method. It has

high BCRs for histogram equalization, compress,

scaling, and small amount of rotation. On the other

hand, the BCRs are rather low for high noise and

cropping of the original image.

5 CONCLUSION

We propose a novel copyright protection technique

by combining features of a watermarking system and

a fingerprinting system. The proposed system

generates extra scrambled information as a function

of original contents and copyright message and

stores it in a certified database for later use. The

generated extra scrambled information in trusted

certification center or database can be used in case

of copyright dispute. The stored extra scrambled

information can be used to identify the copyright

message in many applications.

Since the proposed system can distribute the

original contents without changing any of its values,

no degradation on the contents is introduced. The

experimental results show that the proposed method

performs better than the existing leading method for

various signal processing attacks. In addition, the

computational complexity of the proposed method is

very low so that it can be used for some real time

applications.

We will further study about the extra scrambled

information search algorithms according to

increasing contents and robustness algorithms to

geometric attacks.

REFERENCES

Cox, Ingemar J., 2002. Digital Watermarking(Multimedia

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