Elsevier

Signal Processing

Volume 142, January 2018, Pages 244-259
Signal Processing

Interpolation-based hiding scheme using the modulus function and re-encoding strategy

https://doi.org/10.1016/j.sigpro.2017.07.025Get rights and content

Highlights

  • This study improves Biswapati et al.’s scheme by using modulus function and re-encoding strategy.

  • The proposed scheme reduces the value range of the position values and re-encodes the values to reduce the image distortion.

  • A re-encode function is generated to obtain the rank of the position value in descending order.

  • A mapping function is proposed to map the re-encoded code to the mapping code.

  • The mapping code is half of the re-encoded code such that the image distortion becomes small.

Abstract

Biswapati et al. proposed a interpolation-based hiding scheme. The scheme directly conceals the information, which records the position of the modified pixel to generate the stego-image. The position value is very large, thus creating a large image distortion. This study reduces the value range of the position values and re-encodes the values to reduce the distortion. The proposed scheme examines the probabilities for the position values and re-encodes the value according to its occurrence number. A re-encode function is used to obtain the rank of the position value in descending order. The most frequent position value is re-encoded to zero. The re-encoded codes are positive numbers, and the values of the codes are still large. To narrow down the value, the re-encoded codes are ciphered to generate mapping codes with negative and positive numbers. A mapping function is proposed to map the re-encoded code to the mapping code. The mapping code is half of the re-encoded code such that the image distortion becomes small. The proposed scheme uses different sizes of embedding blocks to control the hiding rate and image quality. Compared with other state-of-the-art methods, the proposed scheme is better in terms of hiding payload and image quality.

Introduction

The information hiding technique is used to share secret messages, detect tampered data, verify ownership, track piracy, and augment data. In an information hiding scheme, cover media, such as image, video, text, execution file, and audio, could be used to carry the secret message. The media that carries the message is called a stego-media. Unauthorized persons cannot detect any difference between the cover media and the stego-media. This study uses an image as the cover media to conceal the secret message for generating the stego-image [8], [10].

Information hiding schemes can be categorized into two types, namely, reversible and non-reversible, according to whether the stego-image can be reversed or not. The reversible data-hiding (RDH) scheme can recover the original image after the concealed message is extracted. Conversely, the non-reversible hiding scheme cannot recover the stego-image to its original state. Research has proposed many related schemes given that the RDH technique can be used in many applications, such as military use, medical purposes, and digital archiving. Recent RDH schemes include histogram shifting, difference expansion, dual images, and image interpolation.

The difference expansion (DE) technique computes the distance between two pixels (or prediction value and pixel) and conceals secret bits into any two-time distances. Tian [10], Alattar [1], and Li et al. [7] proposed DE-based RDH methods to generate the stego-image. DE-based RDH schemes can effectively embed secret information in the cover image. However, this technique can cause great distortion, which diminishes the image quality of the stego-image.

Histogram-shifting hiding techniques are proposed to improve the quality of the stego-image using the DE method. The histogram technique computes the probability of pixels to generate a histogram and points out the peak pixel in the histogram to embed the information. The other pixels between the peak pixel and a zero pixel are shifted to create a space for hiding the secret message. For example, Ni, and Lee et al. proposed histogram-shifting-based hiding schemes [8], [6]. The image quality of the histogram-shifting-based scheme is high, but the embedding payload is low.

Dual-image-based techniques were proposed in 2014 to enhance the embedding payload. The dual-image-based RDH scheme replicates the original image to generate two copy images and conceals information in two images. For example, Qin et al. applied the modulus function and exploited the modification direction and three embedding rules to generate two stego-images [17]. Lu et al. utilized the center-folding strategy to fold the secret message before concealing it in the stego-image to enhance the image quality [13]. Nevertheless, the major drawback of this technique is that it requires two images to extract the message.

One technique to solve this problem is image interpolation, which extends an extra pixel between two neighboring pixels to embed the secret message instead of generating another image. Many researchers proposed interpolation-based RDH schemes to increase the embedding capacity [2], [11], [12], [14], [15], [16]. For example, Malik et al. proposed an image interpolation-based RDH scheme using pixel value adjusting feature [14]. Lee et al. proposed a data-hiding method based on reduplicated exploiting modification direction, image interpolation, and canny edge detection [11]. Lu applied the center-folding strategy and interpolation technique with neighboring pixels (INP) to propose an adaptive interpolation-based hiding scheme. In this scheme, the secret message is folded by the center value to reduce the value range and decrease the image distortion [12]. Biswapati et al. used a weighted matrix to compute the modulus summation to determine which pixel should be modified or not. The position value is added to the interpolated pixel [2].

In Biswapati et al.’s scheme, an original image is divided into several parts with a size of 3 × 3. Then, Biswapati et al. used the interpolation method to generate a cover block size of 5 × 5 for each original part. Each cover block has 12 interpolated pixels, which can be used to conceal 48 secret bits. To enhance the security of the scheme, Biswapati et al. updated the weighted matrix by using a shared secret key. Only authorized personnel who know the secret key can extract the correct message from the stego-image.

In Biswapati et al.’s scheme, the secret message is not directly concealed in the interpolated pixels. A weighted matrix is used to compute the modulus sum and compare the sum with the secret message to make sure the sum is equal to the secret message. If the sum is not equal to the secret message, then the sum is subtracted from the secret message to obtain a modified position value. The position value is then hided into the interpolated pixel to generate the stego-pixel.

Biswapati et al.’s scheme can hide numerous secret messages in the cover image. However, the image quality of Biswapati et al.’s scheme can still be improved.

The key factor that influences the image quality of Biswapati et al.’s scheme is the modified position values. The value is usually very large, thus creating a large image distortion between the interpolated image and the stego-image.

This study reduces the value range of the position values and re-encodes the values to reduce the distortion. The proposed scheme examines the probabilities for the position values and re-encodes the value according to its occurrence number. For the position value with a high occurrence number, the proposed scheme encodes it with a small number close to zero. Conversely, the proposed scheme encodes the rare value with a large number. Frequent position value with a small code can effectively reduce the distortion between the interpolated image and the stego-image.

Furthermore, the proposed scheme uses different sizes of embedding blocks to control the hiding rate and image quality.

Section snippets

Related works

Many types of interpolation techniques, such as neighbor mean interpolation (NMI) and INP, have been proposed. Lu applied INP to expand an image, and Biswapati et al. used NMI to generate virtual pixels.

This study describes NMI (Section 2.1), INP (Section 2.2), Lu's scheme (Section 2.3), and Biswapati et al.’s scheme (Section 2.4) in Section 2.

Proposed scheme

The diagram of the proposed scheme is illustrated in Fig. 8. In the diagram, Fig. 8(a) is the original image. The proposed scheme applies Lee and Huang's INP interpolation method to enlarge the original image for generating the cover image. Fig. 8(b) presents the cover image, which is divided into several blocks. A weighted matrix shown in Fig. 8(c) is used to compute the modulus value. The scheme computes the modulus value for each block and conceals the secret message in the interpolated

Experimental results and discussion

This study compares the proposed scheme with five state-of-the-art methods, namely, NMI (Jung and Yoo [5]), INP (Lee and Huang [6]), CRS (Tang et al. [9]), Lu [12], and Biswapati [2]. Six grayscale images shown in Fig. 14 are used for testing the performance of the proposed scheme. The system is developed by MATLAB R2012a.

The image quality is measured by the peak signal-to-noise ratio (PSNR) computed by PSNR(I)=10×log10[2552MSE](dB),andMSE=1h×wi=0h1j=0w1(I(i,j)I(i,j))2,where h and w are

Conclusion

This study proposes an interpolation-based reversible hiding scheme by using the difference in the re-encoding strategy. The scheme applies the INP interpolation method to enlarge the original image for generating the cover image. The secret message is then concealed in the interpolated pixel. The proposed scheme uses a modulus function and a weighted matrix to compute a modulus value for hiding secret bits. The difference between the modulus value and the secret message is embedded in the

Acknowledgments

This study was financially supported by a research grant from Taiwan's Ministry of Science and Technology (MOST 105-2221-E-324-020).

References (17)

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