Achieve Secure RGB Image Based Watermarking with Pixel Indicator Technique

8thSASTech 2014, Commission IV: New Achievements in Electrical Engineering (NAEEng), Iran, Mashhad, Feb6, 2014

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Achieve Secure RGB Image Based Watermarking with Pixel Indicator Technique

Esmail Mohammadgholi

Malek-Ashtar University of Technology, Tehran, Email: [email protected]

Rahim Entezari Malek-Ashtar University of Technology, Tehran, Email: [email protected]

Alireza Mahdavi

Khajeh Nasir Toosi University of Technology, Tehran, Email: [email protected]

Seyed Mojtaba Hoseini Assistant professor, Malek-Ashtar University of Technology, Tehran, Email: [email protected]

Abstract Digital watermarking is a growing research area to mark digital content. There are a lot of technique in watermarking that use as image as cover media. The common technique used in image watermarking is replaces the least significant bits of image with message. We have introduced the concept of method that use of pixel indicator technique which was introduced by Adnan Gutubin order to increase the capacity of watermarking and PSNR. It can be used for increasing the security of steganographic techniques that embed text bits into RGB images. Key words: Watermarking, Steganography, Pixel indicator, RGB Image 1. Introduction Digital watermarking can be used in wide variety of applications: broadcast monitoring, owner identification, proof of ownership, transaction tracking, authentication, copy control and etc. Historically, the first steganographic techniques included invisible writing using special inks or chemicals[1]. It was also fairly common to hide messages in text. By recovering the first letters from words or sentences of some innocent looking text, a secret message was communicated. Today, it seems natural to use binary files with certain degree of irrelevancy and redundancy to hide data. Digital images, videos, and audio tracks are ideal for this purpose. Watermarking is the practice of hiding a message about an image, audio, video or other work of media within that work itself [1].there are different between steganography and watermarking. Watermarking as the practice of imperceptibly altering a work to embed a message about the work, but steganography as the practice of undetectably altering a work to embed a secret message[1], or steganography is the art and science of hiding information by


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embedding data into media[2]. It is very important differences that some people do not pay attention to it. A generic watermarking system has illustrated in Figure 1.

Figure 1:A generic watermarking system[1] Each steganographic technique consists of an embedding algorithm and a detector function. The embedding algorithm is used to hide secret messages inside a cover. The embedding process is usually protected by a keyword so that only those who posses the secret keyword can access the hidden message. The detector function is applied to the carrier and returns the hidden secret message. For secure covert communication, it is important that by injecting a secret message into a carrier document no detectable changes are introduced[3]. Thus, each watermarking process has two stages: embedding process and extraction process. In this paper, we propose a new method using RGB image pixels as its cover work. This method increases watermark capacity compared to previous work[4]. Watermarking techniques satisfy three characteristics which are Capacity, Robustness and Transparency. These requirements are represented by the magic triangle shown in Figure 2.

Figure 2: Magic triangle Definition 1 (Capacity): The steganography capacity is the maximum number of bits that can be hidden in a given cover work, such that the probability of detection by an adversary is negligible[1]. Definition 2 (Robustness): Robustness refers to the ability to detect the watermark after common signal processing operations[1]. Definition 3 (Invisibility): Invisibility is the state of an object that cannot be seen. In steganography that means the stego image does not raise any suspicion of eavesdroppers.

Embedder Detector

Cover work

Payload Stego work

Detected Payload

Capacity

Invisibility Robustness


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The body of the paper begins with the Introduction. In section 2, pixel indicator technique is introduced. In section 3, related watermarking methods are described. In section 4, we propose a method to increase watermark capacity. Results and Analysis are examined in section 5. The conclusions are presented in section 6. 2. Pixel Indicator Technique In pixel indicator technique1, information is hidden into two of RGB pixel channels based on the indication within the third channel. The pixel indicator technique uses least two significant bits of one of the channels. These channels are Red, Green and Blue. The indicator relation with the hidden data and the two other channels is shown in Table 1.

Indicator channel Channel 1 Channel 2 00 No hidden data No hidden data 01 No hidden data 2bits of hidden data 10 2bits of hidden data No hidden data 11 2bits of hidden data 2bits of hidden data

Table 1: Indicator values based action Operation and channel selection is as follows:

1) The payload length (N) is determined.Table 2, indicator channel is selected. Then other two channels are determined.

2) The message according to Table 1, placed in two channels.

Payload length(N) Indicator channel Arrangement of two channels Odd parity Even parity

Even R GB BG Prime B RG GR Else G RB BR

Table 2: Channel selection 3. Related work

The most of watermarking technique use a LSB method to data hiding. All the LSBs of pixels of cover work can be used for hiding the secret bits. The hidden information can easily be uncovered using statistical steganalysis techniques such as histogram attack or X2 [5]. Many of the research recently published about increasing watermarking capacity[6], [7], [8], [9], [10], [11], [12] and etc. Also there are several paper that are related to PIT[13], [14], [15], [16], [17] . In 2006 a way to add security to the high capacity LSB image steganography was introduced by Neeta at el[18]. This technique is stego color cycle (SCC). This technique cyclically uses different channels of the RGB image pixels to hide the data. In 2010, Adnan Gutub proposed pixel indicator technique to increase the capacity of SCC without degrading the security[4]. This method uses two channels for data hiding. To choose the first indicator channel, the size stored in the first 8 bytes. Then according to Table 2, channels are selected. The indicator choice is assumed as the first level. All six possible selections are obtained from the length of message (N). Messages are embedded into cover work according to Table 1.

1 PIT


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4. Proposed method We have further developed two steganographic methods designed to achieve high capacity and embed text bits into images. Both techniques were tested on Matlab R2012a. In this section, we proposed an improved method to increase capacity by pixel indicator technique. We use this method for hiding the text in the image with two methods. Whole of pixel indicator technique that mentioned above are used in our method with a new approach. These two techniques are shown in blow:

1) The first method (2 bit): According to above description, first we choose indicator channel and two other channels. The channel is selected from table 2. Last two bits of indicator channel are specified. In our method, we embed payload with following method:

The last two bit of indicator channel varies with equal probability. Two bits that altered, according to Table 1 are ready embedding process. Payload is embedded into bits that modified.

2) The first method (1 bit): ASCII1 codes represent text in computers, and other devices

that use text. The ASCII code became common to use an 8-bit byte to store each character in memory, providing an opportunity for extended, 8-bit, relatives of ASCII. These codes usually send in terms of 8bit that concludes parity bit. Because one bit as a final bit is wasted, we first cut bits in the form single bit. Then seventh bit of this character and first bit of next character, together they make up a 2bit. Then according to Table 1, embedding process is done. This idea is shown in Figure 3.

Figure 3: The idea behind ASCII codes 5. Simulation Results and Analysis We simulated the presented method using computational software Matlab R2012a. First we compare the cover image with the stego image based on histogram of images. Figure 4 shows Cover image that we used.

1 American Standard Code for Information Interchange(ASCII)

ASCII code ASCII code

Modified code


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Figure 4: Cover image Figure 5 shows Stego image that we used.

Figure 5: Stego image


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The histogram of cover and stego image are shown in Figure 6.

Figure 6: Histogram of images: a) Cover b) Stego

Then, we illustrate the difference between histograms of cover image and stego image by Exclusive or operation. The Figure 7, shows this specifications.

Figure 7: Xor images The histogram of the cover and stego images are split into Red, Green, Blue channels images with three histograms compared. The Figure 8 shows the histograms of Red channel before and after the embedding process.

b) a)


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Figure 8: Red channel a) Before embedding process.

b) After the embedding process. The Figure 9 shows the histograms of Green channel before and after the embedding process.

Figure 9: Green channel a) Before embedding process.

b) After the embedding process.

b)

a)

b) a)


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The Figure 10 shows the histograms of Blue channel before and after the embedding process.

Figure 10: Blue channel a) Before embedding process.

b) After the embedding process. In order to prove the feasibility of our method that can raise the capacity of hiding with an acceptable quality of the stego image, we measure and evaluate our method by PSNR1. We utilized the PSNR value to evaluate the quality of the stego image. The equation is defined as follows:

[ ]

10

2

PSNR 10 logMAXMSE

(1)

Where MAX is the maximum pixel value of the image. In the case of 8 bits gray scale images the MAX value will be 255.

MSE3

R G BMSE MSE MSE (2)

PSNR evaluation of the images for one bit embedded is shown in following Table 3:

Method All pixels Used pixels Percent used PSNR Our method 196608 57788 29.3925 50.6493

Table 3: PSNR for one bit 1 Peak signal-to-noise ratio(PSNR)

a) b)


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PSNR evaluation of the images for 2 bit embedded is shown in following Table 4:

Method All pixels Used pixels Percent used PSNR Our method 196608 39431 20.0556 52.9782

[16] - - - 50.79 Table 4: PSNR for two bit

Mean and standard deviation for one bit are shown in Table 5:

Method Cover-red Stego-red Cover-green Stego-green Cover-blue Stego-blue Mean

(our method) 140.5987 140.6883 116.2741 116.1450 90.9641 90.8264

Standard deviation

(our method)

76.5908 76.6366 76.4191 76.3537 74.0091 73.8909

Adnan[4] Cover-red Stego-red Cover-green Stego-green Cover-blue Stego-blue Mean 140.695 140.683 116.266 116.261 90.710 90.694

Standard deviation

76.646 76.645 76.574 76.570 74.451 74.411

Table 5: Mean &STD for one bit

Mean and standard deviation for 2 bit are shown in Table 6:

Method Cover-red Stego-red Cover-green Stego-green Cover-blue Stego-blue Mean 140.5987 140.6012 116.2741 116.2511 90.9641 90.9363

Standard deviation

76.5908 76.5951 76.4191 76.4048 74.0091 73.9701

Table 6: Mean & STD for two bit

6. Conclusions and future work In this paper, we study steganographic techniques for images by use of pixel indicator techniques. We have introduced the concept of steganography, watermarking and pixel indicator technique. Then we proposed two new method in RGB image based steganography that use this technique. This technique designed an efficient algorithm that leads to high capacity and PSNR in steganography, that is a important factor in magic triangle. Simulation result demonstrates that our method performs better than other algorithm. Thus, it can be used for increasing the security of steganography techniques that embed text bits into RGB images. In future work, can be used audio, image, video as payload to embedding process. This is a very interesting field in steganography and watermarking. The various steganographic need to be focused on hiding capacity, detectability, level of visibility and robustness against malicious and unintentional attacks.


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[14] N. Tiwari, and M. Shandilya, “Secure RGB Image Steganography from Pixel Indicator to Triple Algorithm-An Incremental Growth,” International Journal of Security and Its Applications, vol. 4, no. 4, pp. 53-62, 2010.

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[18] D. Neeta, K. Snehal, and D. Jacobs, "Implementation of LSB steganography and its evaluation for various bits." pp. 173-178.

Achieve Secure RGB Image Based Watermarking with Pixel Indicator Technique

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