Dynamic embedding strategy of VQ-based information hiding approach Source : Journal of Visual Communication and Image Representation, vol. 59, pp. 14-32, February 2019 Authors : Cheng-Ta Huang, Li-Chiun Lin, Cheng-Hsing Yang and Shiuh-Jeng Wang Speaker : Chia-Shuo Shih Date : 2019/02/28 1

Outline Introduction Related work Proposed method Experimental results Conclusions 2

Introduction(1/2)-data hiding Secret bits Original image Stego image 3

Introduction(2/2)-Compression 512 * 512 = 262144(pixels) 262144 * 8 = 2097152(bits) Compression ratio(CR) = 0.5 2097152(bits) 1048756(bits) Original image Compressed image lossy compression lossless compression Data hiding Improve the image quality 4

Related work(1/3)-Vector Quantization VQ is a lossy image coding technique. VQ consists of three procedures: Codebook design Generate a set of representative codewords. The LBG algorithm is the most commonly used method. Image Encoding Image Decoding [34] Y. Linde, A. Buzo, R. Gray, “Algorithm for Vector Quantizer Design”, IEEE Transactions on Communications, vol. 28, no. 1, pp: 84-95, 1980. 5

Related work(2/3)-Vector Quantization Image Encoding Partition the image into non-overlapped image block Find the closest codeword in the codebook for each image block x The index of the closest codeword of x is recorded. Image Decoding Reconstruct each block by the codeword in the codebook of its index. 6

Related work(3/3)-Vector Quantization Codebook 7

Proposed method(1/9) 𝐶 𝑖 𝑊 𝑖 𝑊 𝑖 ′′′ 8 support take out LSB VQ Secret bits Index block 8

Proposed method(2/9) 4 4 … 65 77 78 90 84 66 70 72 79 80 83 75 69 67 Original image 9

Proposed method(3/9) 𝐹 𝑖 10 Codebook size = 512 I = 65 0 0100 0001 2 77 78 90 84 66 70 72 79 80 83 75 69 67 60 70 64 80 78 75 79 74 69 77 76 VQ 𝑊 𝑖 = {15,17,16,20,19,20,18,18,19,37,34,39,35,38,40,38} Image block Index 𝐶 𝑖 = {16,19,19,22,21,16,17,18,19,40,41,37,33,34,33,36} Codebook Index 𝐹 𝑖 65 = 0100 0001 77 = 0100 1101 . 79 = 0100 1111 67 = 0100 0011 72 = 0100 1000 32 = 0100 000 38 = 0100 110 . 39 = 0100 111 67 = 0100 0011 72 = 0100 1000 16 = 0100 00 19 = 0100 11 . 33 = 0100 001 36 = 0100 100 {65,77,78,90,84,66,70,72,79,80,83,75,66,69,67,72} {32,38,39,45,42,33,35,36,39,80,83,75,66,69,67,72} 10

Proposed method(4/9) T = 3 S = [1001111000100010101101111000100011111100] 𝐶 𝑖 = {16,19,19,22,21,16,17,18,19,40,41,37,33,34,33,36} 𝐹 𝑖 = { 0 } 𝑊 𝑖 = {15,17,16,20,19,20,18,18,19,37,34,39,35,38,40,38} 𝑊 𝑖 ′ = { 19 } 𝑊 𝑖 ′ ＝ 𝑊 𝑖 +𝑏, 𝑖𝑓 𝐶 𝑖 > 𝑊 𝑖 𝑊 𝑖 −𝑏, 𝑖𝑓 𝐶 𝑖 < 𝑊 𝑖 𝑊 𝑖 ,𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒 𝐶 1 = 16 𝑊 1 = 15 𝐹 1 = 0 S = [10] S = [100] S = [1001] S = [1] 𝑊 1 ′ = 19 𝑊 1 + S ≦ 𝐶 1 + T 15 + 1 ≦ 16 + 3 𝑊 1 + S ≦ 𝐶 1 + T 15 + 2 ≦ 16 + 3 𝑊 1 + S ≦ 𝐶 1 + T 15 + 4 ≦ 16 + 3 𝑊 1 + S ≦ 𝐶 1 + T 15 + 9 ≦ 16 + 3 11

Proposed method(5/9) T = 3 S = [100 11 110 00100010101101111000100011111100] 𝐶 𝑖 = {16,19,19,22,21,16,17,18,19,40,41,37,33,34,33,36} 𝐹 𝑖 = { 0,0,0,1 } 𝑊 𝑖 = {15,17,16,20,19,20,18,18,19,37,34,39,35,38,40,38} 𝑊 𝑖 ′ = { 19,20,22,23 } 𝑊 𝑖 ′ ＝ 𝑊 𝑖 +𝑏, 𝑖𝑓 𝐶 𝑖 > 𝑊 𝑖 𝑊 𝑖 −𝑏, 𝑖𝑓 𝐶 𝑖 < 𝑊 𝑖 𝑊 𝑖 ,𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒 𝐶 4 = 22 𝑊 4 = 20 𝐹 4 = 1 S = [0] 𝑆 ′ = [1] S = [00] 𝑆 ′ = [11] S = [001] 𝑆 ′ = [110] 𝑊 4 + 𝑆 ′ ≦ 𝐶 4 + T 20 + 1 ≦ 22 + 3 𝑊 4 + 𝑆 ′ ≦ 𝐶 4 + T 20 + 3 ≦ 22 + 3 𝑊 4 + 𝑆 ′ ≦ 𝐶 4 + T 20 + 6 ≦ 22 + 3 𝑊 4 ′ = 23 12

Proposed method(6/9) T = 3 S = [100 11 110 00 100 010 10 1101111000100011111100] 𝐶 𝑖 = {16,19,19,22,21,16,17,18,19,40,41,37,33,34,33,36} 𝐹 𝑖 = { 0,0,0,1,0,1,0,1 } 𝑊 𝑖 = {15,17,16,20,19,20,18,18,19,37,34,39,35,38,40,38} 𝑊 𝑖 ′ = { 19,20,22,23,23,15,16,18 } 𝑊 𝑖 ′ ＝ 𝑊 𝑖 +𝑏, 𝑖𝑓 𝐶 𝑖 > 𝑊 𝑖 𝑊 𝑖 −𝑏, 𝑖𝑓 𝐶 𝑖 < 𝑊 𝑖 𝑊 𝑖 ,𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒 𝐶 8 = 18 𝑊 8 = 18 𝑊 8 = 𝑊 8 ′ = 18 S = [1] 𝐹 8 = 1 13

Proposed method(7/9)-The extracting process 𝑊 𝑖 ′ = {19,20,22,23,23,15,16,18,19,41,40,36,31,34,33,34 } 𝐹 𝑖 = { 0,0,0,1,0,1,0,1,1,1,0,1,0,1,0,0 } I = 0 0100 0001 2 𝑊 𝑖 ′ 6 𝑜𝑟 7𝑏𝑖𝑡𝑠 + 𝐹 𝑖 1𝑏𝑖𝑡 = 𝑊 𝑖 ′′ (7 𝑜𝑟 8𝑏𝑖𝑡𝑠) 𝑊 1 ′ =19(010011) + 𝐹 1 = 0 = 𝑊 1 ′′ =0100110(38) 𝑊 10 ′ =41(0101001) + 𝐹 10 = 1 = 𝑊 10 ′′ =01010011(83) 𝑊 𝑖 ′′ = {38,40,44,47,46,31,32,37,39,83,80,73,62,69,66,68} 𝑊 𝑖 ′′ 7𝑏𝑖𝑡𝑠 + 𝐼 1𝑏𝑖𝑡 = 𝑊 𝑖 ′′′ (8𝑏𝑖𝑡𝑠) 𝑊 1 ′′ =38(0100110) + 𝐼 = 0 = 𝑊 1 ′′′ =01001100 76 𝑊 𝑖 ′′′ = {76,80,89,94,92,62,64,74,79,83,80,73,62,69,66,68} 14

Proposed method(8/9)-The extracting process 𝑊 𝑖 ′′′ = {76,80,89,94,92,62,64,74,79,83,80,73,62,69,66,68} 𝑊 1 ′′′ = 76(01001100) (0100110) I = (0) 𝑊 2 ′′′ = 80(01010000) (0101000) I = (00) . 𝑊 9 ′′′ = 79(01001111) (0100111) I = (0 0100 0001) 𝑊 𝑖 ′′ = {38,40,44,47,46,31,32,37,39,83,80,73,62,69,66,68} 𝑊 𝑖 ′ = {19,20,22,23,23,15,16,18,19,41,40,36,31,34,33,34 } 𝐹 𝑖 = { 0,0,0,1,0,1,0,1,1,1,0,1,0,1,0,0 } 60 70 64 80 78 75 79 74 69 77 76 Codebook Index 𝑊 𝑖 = {15,17,16,20,19,20,18,18,19,37,34,39,35,38,40,38} 15

Proposed method(9/9)-The extracting process 𝑊 𝑖 = {15,17,16,20,19,20,18,18,19,37,34,39,35,38,40,38} 𝑊 𝑖 ′ = {19,20,22,23,23,15,16,18,19,41,40,36,31,34,33,34 } 𝐹 𝑖 = { 0,0,0,1,0,1,0,1,1,1,0,1,0,1,0,0 } 𝐷 ′ = | 𝑊 𝑖 ′ − 𝑊 𝑖 | 𝑊 1 ′ − 𝑊 1 =19 −15=4 100 𝐹 1 =0 , 𝑆=100 𝑊 4 ′ − 𝑊 4 =23 −20=3 11 𝐹 4 =1 , 𝑆=00 𝑊 8 ′ − 𝑊 8 =18 −18=0 𝐹 8 =1 , 𝑆=1 S = [100 11 110 00 100 010 10 1 1 011 110 00 100 011 111 100] 16

Experimental results(1/6) 17

Experimental results(2/6) PSNR (dB) EC (bits) t 128 256 512 1024 39.76 40.51 40.85 41.11 508,571 455,625 433,687 414,215 1 39.75 40.54 40.86 508,587 455,692 433,654 414,200 2 39.77 40.53 41.09 508,523 455,563 433,681 414,207 3 39.68 40.41 40.72 41.00 516,349 464,347 441,685 421,240 4 39.39 40.06 40.40 40.68 530,220 478,194 454,103 431,922 5 38.88 39.48 39.85 40.17 545,077 492,272 466,581 442,910 6 38.24 38.80 39.19 39.56 559,125 505,526 478,164 452,784 7 37.56 38.12 38.54 38.95 571,356 516,170 487,565 460,821 8 36.76 37.32 37.75 38.20 587,778 531,407 501,852 474,221 9 35.95 36.51 36.96 37.44 599,878 542,109 510,983 482,190 10 35.08 35.62 36.09 36.56 616,456 557,886 526,264 496,980 11 34.32 34.85 35.35 35.85 627,452 567,713 534,810 504,223 12 33.51 34.01 34.49 34.99 645,617 585,524 552,235 521,444 13 32.84 33.34 33.84 34.36 655,183 593,935 559,624 527,792 14 32.15 32.63 33.11 33.62 670,523 609,070 574,836 542,747 15 31.61 32.64 33.17 678,227 615,327 580,263 547,541  Average PSNR and EC with each threshold t. 18

Experimental results(3/6) 19

Experimental results(4/6) 256 PSNR (dB) EC (bits) t = 0 Huang’s Ours Delta Airplane 33.73 42.25 8.52 429,569 375,734 −53835 Baboon 27.55 37.16 9.61 704,569 567,010 −137559 Boat 33.21 41.47 8.26 490,188 411,482 −78706 Goldhill 34.25 42.03 7.78 552,546 441,132 −111414 Lena 34.86 42.78 7.92 454,996 380,976 −74020 Average 32.72 41.14 8.42 526,374 435,267 −91107 t = 12 34.45 0.72 511,084 81,515 33.44 5.89 676,059 −28510 34.20 0.99 548,866 58,678 34.16 −0.09 579,319 26,773 34.29 −0.57 524,093 69,097 34.11 1.39 567,884 41,511 t = 15 32.50 −1.23 539,583 110,014 31.83 4.28 704,221 −348 32.26 −0.95 579,269 89,081 32.14 −2.11 611,392 58,846 32.32 −2.54 554,907 99,911 32.21 −0.51 597,874 71,501 Comparison with Huang’s two-level encoding. 20 C.-T. Huang, M.-Y. Tsai, L.-C. Lin, W.-J. Wang, S.-J. Wang”VQ-based data hiding in IoT networks using two-level encoding with adaptive pixel replacements”J. Supercomput. (2016), pp. 1-20

Experimental results(5/6) 21 W.-J. Wang, C.-T. Huang, S.-R. Tsuei, S.-J. Wang”A greedy steganographic SMVQ approach of greedy-USBIRDS using secret bits for image-block repairing based on differences” Multimed. Tools Appl., 75 (22) (2016), pp. 14895-14916

Experimental results(6/6) 22 W.-J. Wang, C.-T. Huang, S.-R. Tsuei, S.-J. Wang”A greedy steganographic SMVQ approach of greedy-USBIRDS using secret bits for image-block repairing based on differences” Multimed. Tools Appl., 75 (22) (2016), pp. 14895-14916

Conclusions Improve embedding capacity and image quality. dynamic-length secret bits. 23

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