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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