Improvement of Multi-bit Information Embedding Algorithm for Palette-Based Images

Anu Aryal, Kazuma Motegi, Shoko Imaizumi and Naokazu Aoki Division of Advanced Integration Science

Chiba University, Japan

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ISC 2015, 11th September, 2015

Outline

Background

Current Research

Results

Conclusion

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Outline

Background

Current Research

Results

Conclusion

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Introduction

Steganography [1] is the art and science of hiding information by embedding it in some other data.

Unauthorized recipients unaware about the existence of embedded data.

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[1] Kahn, D.: The history of steganography. In: Goos, G., Hartmanis, J. (eds.) The First International Workshop on Information Hiding. LNCS, vol.1174, pp.1-5, Springer, Heidelberg (1996).

Conventional method [2] Embeds each k-bits message into pixels of 2 × 2 pixel matrix as

shown in Fig. 1. Based on embedding a message into the pixels by assigning a parity to

each pixel matrix according to the Euclidean distance.

Fig. 1. Embedded unit of Conventional Method [2].

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[2] Imaizumi, S., Ozawa, K.: Palette-Based Image Steganography for High-Capacity Embedding. Bull. Soc. Photogr. Imag. Japan, Vol.25, No. 1, pp.7-11 (2015).

Conventional method [2] contd.Drawbacks At maximum, only 3/4 bit per pixel can be embedded.

Maximum embedded amount is smaller than those methods that embed one bit message into one pixel [3-6].

Tendency to occur large color difference that leads to image degradation.

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[2] Imaizumi, S., Ozawa, K.: Palette-Based Image Steganography for High-Capacity Embedding. Bull. Soc. Photogr. Imag. Japan, Vol.25, No. 1, pp.7-11 (2015).[3] Tzeng, C.-H., Yang, Z.-F., Tsai, W.-H.: Adaptive data hiding in palette images by color ordering and mapping with security protection. IEEE Trans. Commun. 52(5), 791-800 (2004).[4] Fridrich, J.: A new steganographic method for palette-based image. In: Proc. Of IS&T PICS, pp.285-289 (1999).[5] Huy, P.T., Thanh, N.H., Thang, T.M., Dat, N.T.: On fastest optimal parity assignments in palette images. In: Intelligent Information and Database Systems,vol. 7197, pp. 234-244 (2012).[6] Inoue, K., Hotta, S., Takeichi, Y., Urahama, K.: A Steganographic Method for Palette-Based Images [in Japanese]. In: The Transactions of the Institute of Electronics, Information and Communication Engineers. A, vol. 82, no.11, pp.1750-1751(1999)

Motivation High capacity of embedding.

Suppression of degradation of image quality.

Conventional method [2] has space to improve both.

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[2] Imaizumi, S., Ozawa, K.: Palette-Based Image Steganography for High-Capacity Embedding. Bull. Soc. Photogr. Imag. Japan, Vol.25, No. 1, pp.7-11 (2015).

Outline

Background

Current Research

Results

Conclusion

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Current Research Concept Embed each k bit message into 1×3 pixel matrix as shown in Fig. 2.

Embed message into a limited color by controlling the index values.

Fig. 2. Embedded unit of proposed method (k = 3).

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Proposed Method (1)

1) Sorting the color palette.

2) Embedding of message.

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Proposed Method (2)1. Sorting color palette using CIEDE2000 [7].

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Find the darkest color in entries Ci.

Set the increment j = j +1.

Calculate ∆ E00 between initial entries Ci and entries C’j-

1.

Indices are assigned to all the entries.

[7] Colorimetry - Part 6: CIEDE2000 Colour-difference formula. ISO/CIE 11664-6 (2014).

Proposed Method (3)2. Embedding of message.

Select 1×3 pixel matrix from the target image (message length is k = 3 bits) as shown in Fig. 2.

Fig. 2. Embedded unit of proposed method (k = 3).

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Proposed Method (4)

Calculate parity Sn as

Sn= d0(n) + dl(n) mod 4, where dl(n) indicates the index of pixel tl(n) .

Fig. 2. Embedded unit of proposed method (k = 3).

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Proposed Method (5)

The value of Sn can be controlled by changing the indices of p(n) , t0(n) and t1(n) by +1 or -1.

Fig. 2. Embedded unit of proposed method (k = 3).

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Pn Sn

Embedding Information wn

0 3 70 2 60 1 50 0 41 0 31 1 21 2 11 3 0

Table 1. Example of Pn, Sn and embedded information wn.

Proposed Method (6)

Pn Sn Embedding Information wn

0 3 7

0 2 6

0 1 5

0 0 4

1 0 3

1 1 2

1 2 1

1 3 0

Table 1. Example of Pn, Sn and embedded information wn.

Index of p(n) = Even

Index of p(n) = Odd

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pn

t0(n)

t1(n)

Target matrix

Value of Pn before and after embedding

Index of p(n) ∆ E00

Different Change by +1 or -1 Smaller

Difference between Sn before and after

embedding

Index of t0(n) and t1(n) ∆ E00

2 Change by +1 or -1 Smaller

Difference between Sn before and after

embedding

Index of t0(n) or t1(n) ∆ E00

1 Change by +1 or -1 Smallest

Difference between Sn before and after

embedding

Index of t0(n) or t1(n)

0 Not changed

Proposed Method (7)

Embedded message wn can be extracted after calculating Pn and Sn .

Performs embedding process only when all ∆ E00 values for the pixels of matrix become 5.0 or less else not.

Steps are repeated until all the messages are embedded.

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Proposed Method (8)

Fig. 3. Color blocks and isolated colors.

Each block has been generated by delimiting colors when ∆E00 > 5.0.

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Proposed Method (9)

Proposed Method Conventional Method [2]

Fig. 4. Matrix arrangement for maximum amount of embedded bits.Fig. 5. Matrix arrangement for minimum amount of embedded bits.

Proposed Method Conventional Method [2]

Maximum amount of embedded bits. Minimum amount of embedded bits.

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[2] Imaizumi, S., Ozawa, K.: Palette-Based Image Steganography for High-Capacity Embedding. Bull. Soc. Photogr. Imag. Japan, Vol.25, No. 1, pp.7-11 (2015).

Outline

Background

Current Research

Results

Conclusion

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Experimental Setups Amount of embedded bits: 10,800 and 21,600 bits.

Used images: 256×256 pixels, 8-bit color bitmap images.

Number of images: 12

Image quality metrics: PSNR and SSIM.

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Structural Similarity (SSIM) [8]SSIM is introduced to measure the quality of distored images.SSIM has Luminance Comparison l(x,y), Contrast comparison

c(x,y) and Structure comparsion s(x, y). Therefore,

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Fig. 6 Diagram of SSIM measurement system.

[8] Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: From error visibility to structural similarity. In: IEEE Trans. on Image Processing.13 (4), pp.600-612 (2004)

Simulation Result (I)

Original (Pepper)

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Proposed method (10,800 bits)

SSIM = 0.871

PSNR = 40.34

Conventional method (10,800 bits)

SSIM = 0.831

PSNR = 36.58

Simulation Result (I)

Original (Pepper)

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Proposed method (21,600 bits)

SSIM = 0.754

PSNR = 37.19

Conventional method (21,600 bits)

SSIM = 0.699

PSNR = 33.67

Simulation Result (III)

Original (Balloon)

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Proposed method (10,800 bits)

SSIM = 0.867

PSNR = 43.49

Conventional method (10,800 bits)

SSIM = 0.822

PSNR = 40.73

Simulation Result (IV)

Original (Balloon)

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Proposed method (21,600 bits)

SSIM = 0.751

PSNR = 40.62

Conventional method (21,600 bits)

SSIM = 0.674

PSNR = 37.68

Quantitative Evaluation (I)

10,800 bits 21,600 bits

Fig. 7. Evaluation using PSNR.

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Quantitative Evaluation (II)

10,800 bits 21,600 bits

Fig. 8. Evaluation using SSIM.

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Quantitative Evaluation (III)

Embedded bits Proposed Method Conventional method [2]

Maximum bits 65, 280 49,152

Minimum bits 39,168 21,675

Table 2. Maximum and minimum values of embedded bits. .

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[2] Imaizumi, S., Ozawa, K.: Palette-Based Image Steganography for High-Capacity Embedding. Bull. Soc. Photogr. Imag. Japan, Vol.25, No. 1, pp.7-11 (2015).

Outline

Background

Current Research

Results

Conclusion

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Conclusion Enhances data embedding with larger capacity.

- Maximum amount of embedded bits is 1.3 times and Minimum amount is 1.8 times more than conventional method.

Improves the image quality by suppressing image quality degradation.

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Thank you

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