1.1 Block diagram for binary error diffusion. The pixel f (m, n) is passed through a quantizer to obtain the corresponding pixel of the halftone g(m, n). The difference between these two pixels is diffused to the neighboring pixels by means of the filter h(k, l). (Reprinted with permission from IEEE Trans. Inf. Forensics Security, vol. 4, no. 3, pp. 383–396, Sep. 2009 ©IEEE 2009) 3
1.2 Floyd-Steinberg error filter. • indicates the current pixel. The weights are given by: h(0,1) = 7/16, h(1, −1) = 3/16, h(1, 0) = 5/16 and h(1, 1) = 1/16. (Reprinted with permission from IEEE Trans. Inf. Forensics Security, vol. 4, no. 3, pp. 383–396, Sep. 2009 ©IEEE 2009) 4
1.3 In a 2-out-of-2 scheme, a secret pixel is encoded into 2 subpixels in each of the two shares. (Reprinted with permission from IEEE Trans. Inf. Forensics Security, vol. 4, no. 3, pp. 383–396, Sep. 2009 ©IEEE 2009) 6
1.4 Example of 2-out-of-2 scheme. The secret image (a) is encoded into two shares (b)-(c) showing random patterns. The decoded image (d) shows the secret image with 50% contrast loss. (Reprinted with permission from IEEE Trans. Inf. Forensics Security, vol. 4, no. 3, pp. 383–396, Sep. 2009 ©IEEE 2009). 7
1.5 Example of halftone cells in a 2-out-of-2 scheme using the first method. The 1st and the 2nd pixels in both shares are SIPs. The 3rd pixel in share 1 and the 4th pixel in share 2 are ABPs. Others (”X”) are assigned to carry visual information. (Reprinted with permission from IEEE Trans. Inf. Forensics Security, vol. 4, no. 3, pp. 383–396, Sep. 2009 ©IEEE 2009). 10
1.6 Upper left: distributions Zi, i = 0,1,…, 3. □ indicates pixels within Z0; •i indicates pixels within Zi. Upper right: distribution of SIPs and ABPs in share 1. Down left: distribution of SIPs and ABPs in share 2. Down right: distribution of SIPs and ABPs in share 3. •i indicates ABP and Δ indicates pixels used to carry share visual information. (Reprinted with permission from IEEE Trans. Inf. Forensics Security, vol. 4, no. 3, pp. 383–396, Sep. 2009 ©IEEE 2009). 13
1.7 Composition of shares. □ indicates SIPs; 1 indicates ABPs; Δ indicates pixels to carry the share visual information. Reprinted with permission from IEEE Trans. Inf. Forensics Security, vol. 4, no. 3, pp. 383–396, Sep. 2009 ©IEEE 2009). 14
1.8 Block diagram of halftone VSS using the first method. Depending on the secret image and VSS scheme chosen, the SIP assignment block outputs the SIPs. If gi(m,n) is a SIP or ABP, its value is prefixed. Otherwise, gi(m,n) is determined by the output of the thresholding block. (Reprinted with permission from IEEE Trans. Inf. Forensics Security, vol. 4, no. 3, pp. 383–396, Sep. 2009 ©IEEE 2009) 15
1.9 (a) Grayscale image Lena. (b) Part of the distribution of SIPs and ABPs. The gray pixels indicate SIPs and the black pixels indicate ABPs. (Reprinted with permission from IEEE Trans. Inf. Forensics Security, vol. 4, no. 3, pp. 383-396, Sep. 2009 ©IEEE 2009). 20
1.10 (a)–(c) Shares of the 3-out-of-3 scheme using the first method, q = 9. The perceived errors are 1.73 × 1010, 8.45 × 109, and 5.46 × 109, respectively. (d) Decoded image by shares (a)-(c), α = 1/9. (Reprinted with permission from IEEE Trans. Inf. Forensics Security, vol. 4, no. 3, pp. 383–396, Sep. 2009 ©IEEE 2009). 22
1.11 (a)–(c) Shares of the 3-out-of-3 scheme using the first method, q = 16. The perceived errors are 7.1 × 109, 3.48 × 109, and 2. 27 × 109, respectively. (d) Decoded image by shares (a)-(c), α = 1/16. (Reprinted with permission from IEEE Trans. Inf. Forensics Security, vol. 4, no. 3, pp. 383–396, Sep. 2009 ©IEEE 2009) 23
1.12 (a)–(c) Shares of the 3-out-of-3 scheme using the second method, q = 16. (d) Decoded image by shares (a)–(c), α = 1 / 16. (Reprinted with permission from IEEE Trans. Inf. Forensics Security, vol. 4, no. 3, pp. 383–396, Sep. 2009 ©IEEE 2009) 24
1.13 (a)–(c) Another set of shares generated by the second method, q = 16, depicting more pronounced artifacts. (Reprinted with permission from IEEE Trans. Inf. Forensics Security, vol. 4, no. 3, pp. 383–396, Sep. 2009 ©IEEE 2009) 25
2.1 Pixels superposition: black and white (left) and colored (right) 33
2.2 Electromagnetic spectrum 33
2.3 Additive color model with primaries red, green, and blue 34
2.4 Subtractive color model with primaries cyan, magenta, and yellow 35
2.5 Examples of pixels superposition 37
2.6 More examples of pixels superposition 37
2.7 Lattice for the RGB and CMY color models 38
2.8 The darkening problem 39
2.9 The VV trick for the case of 4 colors. Subpixels with different colors are never superposed 45
3.1 Implementation results of visual one-secret sharing in two shares: (a) P, (b) S1, (c) S2, (d) S1 ⊗ S2 61
3.2 Encoding S1 in Wu and Chen’s scheme: (a) Four triangle-like areas. (b) Indexing the blocks in each of the four areas. (c) Blocks to be assigned. 64
3.3 Example for illustrating the idea of Wu and Chen [12]: (a) P1, (b) P2, (c) S1, (d) S2, (e) S1 ⊗ S2, ⊗ S2 65
3.4 2 × 2 sector blocks for A in Wu and Chang’s approach: (a) 2 × 2 sector blocks for A, (b) prev(s) and next(s) of sector block s 66
3.5 Decomposing circle shares A and B into chords, which are further divided into blocks: (a) A, (b) B 70
3.6 Elementary blocks for circle share A for sharing 3 secrets: (a) 71
3.7 Subpixels in 2 × 3 elementary block s and permute(s, Σ): (a) a certain ordering of the subpixels in s, (b) the ordering of those in permute(s, Σ) where Σ = (3, 5,1, 6, 2, 4) 71
3.8 Encoding the first three blocks in each of the three chords by Σ1 in A: (a) A, (b) A120°, (c) A240° 72
3.9 Absolute location of block [1, j], [2, j], and [3, j] 73
3.10 Elementary blocks of share B for sharing 3 secrets: 74
3.11 Instances of the first three pixels of the three strips in (a) P1, (b) P2, and (c) P3 75
3.12 Encoding in B 75
3.13 Encoding in B 77
3.14 Encoding in B 79
3.15 Results of (a) A ⊗ B, (b) A120° ⊗ B, and (c) A240° ⊗ B 79
3.16 Elementary block for x secrets 80
3.17 Elementary blocks in 81
3.18 Elementary blocks in 82
3.19 Stacking results of the chosen visual patterns for Feng et al.’s scheme. 84
3.20 Implementation results for the proposed visual 3-secret sharing scheme: (a) P1, (b) P2, (c) P3, (d) A, (e) B, (f) A ⊗ B, (g) A120° ⊗ B, (h) A240° ⊗ B, (i) A85° ⊗ B 86
3.21 Implementation results for the proposed visual 3-secret sharing scheme with a different starting encoding position: (a) A′, (b) B′, (c) A′ ⊗ B′, (d) (A′)85° ⊗ B′, (e) (A′)205° ⊗ B′, (f) (A′)325° ⊗ B′ 88
3.22 Results of computer implementation for 4-secret sharing: (a) P1, (b) P2, (c) P3, (d) P4, (e) A, (f) B, (g) A⊗B, (h) A90° ⊗ B, (i) A180° ⊗ B (j) A270° ⊗ B 89
3.23 Transforming circle shares (a) and (b) into cylinder counterparts (c) and (d), respectively 90
3.24 Shares (based upon Experiment 1) with supplementary lines to ease the alignments: (a) A with three markers, (b) B with one marker 92
4.1 Six possible patterns of subpixel arrangements with 50% gray. 97
4.2 An example of visual secret sharing scheme (VSSS) 98
4.3 An example of extended visual cryptography scheme (EVCS). 101
4.4 An example of random grid (RG) 102
4.5 Samples of ordered dither matrices 104
4.6 Point process and error diffusion 105
4.7 Error filters for error diffusion 106
4.8 Iterative and search-based method 106
4.9 Dither matrices for similar shadow scheme proposed in [32] 112
4.10 The conjugate error diffusion algorithm proposed in [9] 113
4.11 Examples of subpixel arrangements with enhanced misalignment tolerance 116
4.12 Variation of subpixel arrangement having the same transparency 117
4.13 An example of difference maximization 118
4.14 The possible pattern combinations of subpixel arrangements 118
4.15 Physical implementation of the concentric subpixel arrangements using square patterns 119
4.16 Input images 120
4.17 Examples of resulting images 121
4.18 Examples of the output with density pattern using 3 × 3 122
5.1 A construction for (2,n) Boolean probabilistic VCS 148
5.2 Ulutas et al. [18] construction for (2,n) Boolean probabilistic VCS 149
5.3 A construction for (n, n) Boolean probabilistic VCS 149
7.1 Implementation results of Algorithms 1, 2, and 3 for encrypting binary image B: (a) B; (b), (c), and (d) two encrypted shares and reconstructed image by Algorithm 1; (e), (f), and (g) two encrypted shares and reconstructed image by Algorithm 2; (h), (i), and (j) two encrypted shares and reconstructed image by Algorithm 3 195
7.2 Reconstructed results by Naor and Shamir’s approach for binary image B in Figure 7.1(a): (a) m = 2, (b) m = 4 196
7.3 Binary image B in Experiment 1 208
7.4 Implementation results of Algorithm 4 for VCRG-3 with respect to B: 209
7.5 Implementation results of Algorithm 5 for VCRG-3 with respect to 210
7.6 Implementation results of Algorithm 6 for VCRG-3 with respect to 211
7.7 Results of Algorithm 7 where Encryption_VCRG(H, 3) was implemented by Algorithm 4 with respect to gray-level image G in Experiment 2: (a) G; (b) halftone version H of G; 212
7.8 Reconstructed results of VCRG-3 with respect to 213
7.9 Results of Steps 1 and 2 of Algorithm 8 for VCRG-3 with respect to color image P in Experiment 3: (a) P; (b) Pc, (c) Pm, (d) Py; (e) Pc, (f) Pm, (g) Py 214
7.10 Results of Step 3 of Algorithm 8 with respect to Pm where Eycrypt_c VCRG(Pm, m, 3) was based upon Algorithm 4: 215
7.11 Results of Algorithm 8 for VCRG-3 with respect to P: (a) R1, (b) R2, (c) R3; (d) R1 ⊗ R2, (e) R1 ⊗ R3, (f) R2 ⊗ R3; (g) R1 ⊗ R2 ⊗ R3 (based upon Algorithm 4); (h) R′1 ⊗ R′2 ⊗ R′3 (based upon Algorithm 5); (i) R″1 ⊗ R″2 ⊗ R″3 (based upon Algorithm 6) 216
7.12 Results of Algorithms 4 for VCRG-4 with respect to binary image B: (a) B; (b) R1, (c) R2, (d) R3, (e) R4; (f) R1 ⊗ R2; (g) R1 ⊗ R2 ⊗ R3; (h) R1 ⊗ R2; (g) R1 ⊗ R2 ⊗ R3 ⊗ R4 217
7.13 Results of Algorithms 8 where Encrypt_c VCRG(Px, x, 4) was based upon Algorithm 4 for VCRG-4 with respect to P (Figure 7.9(a)): (a) R1, (b) R2, (c) R3, (d) R4; (e) R1 ⊗ R2; (f) R1 ⊗ R2 ⊗ R3; (g) R1 ⊗ R2 ⊗ R3 ⊗ R4 218
8.1 Example of encoding a visual cryptography scheme 224
9.1 A construction for almost ideal contrast (ΓQual, ΓForb)-VCS with reversing 263
9.2 A construction for ideal contrast VCS with reversing using a BSS 267
9.3 Cimato, De Santis, Ferrara, and Masucci’s ideal contrast VCS with reversing 269
9.4 Hu and Tzeng’s ideal contrast VCS with reversing 272
9.5 Yang, Wang, and Chen’s ideal contrast VCS with reversing 274
9.6 Ideal contrast VCS with reversing starting from any VCS 277
10.1 Visual cryptography 283
10.2 The concept of 2-out-of-2 VC 284
10.3 A 2-out-of-3 visual secret sharing scheme 284
10.4 Cheating in visual cryptography 286
10.5 HCT1 288
10.6 Experiment of HCT1 288
10.7 HCT2 289
10.8 HT 290
10.9 Experiment of HT 291
10.10 TCH 292
10.11 PS1 293
10.12 PS2 293
11.1 The stacking results of the (2,2)-DVCS (a) when no share is shifted; (b) when one share is shifted by one subpixels; (c) when one share is shifted by two subpixel. A printed-text ”CRYPTO” is tested 302
11.2 Recovered secret images of a (2,2)-VCS for three misalignment deviations (a) (dx, dy) = (0, 0), (b) (dx, dy) = (0.5,0), and (c) (dx, dy) = (1, 2) 310
11.3 Stacked results of white pixels (a1: 1W1B+1W1B, a2: 1B1W+1B1W) and black pixels (b1: 1W1B+1B1W, b2: 1B1W+1W1B) for the same deviation (dx, dy) 311
11.4 The regions of deviation (dx, dy) that can recover the secret image 313
11.5 Recovered Lena images for (2,2)-VCS using the different sized subpixels: (a) the small-sized subpixel, (b) the medium-sized subpixel and (c) the large-sized subpixel. 316
11.6 Recovered secret image for a (2, 2)-VCS using two different-sized subpixels and (dx, dy) = (0.5, 0.5), (s1/s2) = 2: (a) the small subpixel and (b) the large subpixel; two secret image (a printed text “VSS” and a halftoned Lena image) are tested. 318
11.7 Regular and random masks for arranging the large and small subpixels: (a) regular mask and (b) random mask 320
11.8 Encrypt a 16 × 16-pixel secret image by using a (2, 2) misalignment VCS, where pB = pS = 50%, γ2 = 4, and Mreg are used: (a) the small-scaled secret image IS, (b) the large-scaled secret image IB, and (c) two shares O(1) and O(2) 322
11.9 Recovered secret images for a (2, 2) misalignment VCS using two-sized subpixels of γ2 = 16: (a) pB = 0%, (b) pB = pS = 50%, Mreg, (c) pB = pS = 50%, Mran and (d) pb = 100%, horizontal deviations: 0, 0. 5, 1, and 2 are tested (unit: small subpixel) 323
11.10 Recovered secret images for a (2, 2) misalignment tolerant VCS using pB = pS = 50%, Mreg and three size ratios: (a) γ2 = 4, (b) γ2 = 16 and (c) γ2 = 64, horizontal deviations: 0, 0. 5, 1, 1 .5, 2, 2. 5, 3, and 3. 5 are tested (unit: small subpixel) 324
12.1 (a) The bank sends the information to be confirmed in an encrypted image to the user’s computer and (b) the user is able read this information using the transparency he got from the bank 330
12.2 A man-in-the-middle manipulation attack by a trojan on an online money transfer 331
12.3 The main method is also applicable to mobile banking 332
12.4 For confirmation, the user has to click the black balls placed between parts of the transaction data 334
12.5 Pixel-based (left) versus segment-based (right) visual cryptography 335
12.6 The main method using segment-based visual cryptography in (a) and (b) 336
12.7 Cardano cryptography: above a 1-factor confirmation (user types 3752), below a 2-factor confirmation (for example, in case his PIN is 1234, the user types in 4136) 337
12.8 (a) To log in, the server sends an encrypted image of a permutated keyboard, which the user can only read after placing the slide over it. (b) The user enters the PIN by clicking at the positions according to their order in the PIN 338
12.9 For confirmation, the user has to click his PIN using a permutation of digits on the right side in (a) and (b) 340
12.10 For confirmation, the user has to click his PIN using inverted numbers 341
12.11 Superimposing two encrypted images for the same key-slide shows the difference of the original picture 342
12.12 This example shows how the view from the observer (A) through prisms (B) is directed to areas 1,2,… or 5 on the encrypted image (C); the deviation depends on the slope of the prism 344
12.13 Some parts of the encrypted image (C) is magnified for the observer (A), while other parts are hidden. For example, d and j are in the focus while b, c, e, f, h, i, k, and l are hidden 345
12.14 Lenses are placed randomly on the slide (b). This can be done by spraying a transparent liquid that becomes hard on the side. The area in the focus of the lenses in the encrypted image (a) is colored in the color of the original image at this region. The rest of (a) is filled such that colors in (a) are equally distributed so that the original image can not be obtained from (a) alone but only together with the slide (b) 345
12.15 Each area of the slide (b) has fragments of lenses, which direct the view (c) in a magnifying manor to one of the symbols on the encrypted text (a) 346
12.16 The voter enters the vote, verifies the image, and separates the slides 347
12.17 Each trustee strips one layer of the doll (represented by the barcode) and uses it to modify the image. The order is randomly permutated 348
13.1 Error diffusion process 353
13.2 Original multitone ”Lena” (X) 354
13.3 Halftone image generated by error diffusion with the Steinberg kernel 355
13.4 Halftone image generated by error diffusion with the Jarvis kernel (Y1) 355
13.5 Secret pattern ”UST” to be embedded in the halftone image (W) 358
13.6 DHSED-generated Y2 (L = 5) of Lena with respect to X in Figure 13.2, W in Figure 13.5, and Y1 in Figure 13.4 358
13.7 Image Y obtained by overlaying Y1 in Figure 13.4 and Y2 in Figure 13.6 359
13.8 The DHCED (Data Hiding by Conjugate Error Diffusion) process 360
13.9 DHCED-generated Y2 (T = 10) of Lena with respect to X in Figure 13.2, W in Figure 13.5, and Y1 in Figure 13.4 363
13.10 Image Y obtained by overlaying Y1 in Figure 13.4 and Y2 in Figure 13.9 364
13.11 Original multitone ”Pepper” (X2) 364
13.12 DHCED-generated Y2 (T = 10) of Pepper with respect to X2 in Figure 13.11, W in Figure 13.5, and Y1 in Figure 13.4 365
13.13 Image Y obtained by overlaying Y1 in Figure 13.4 and Y2 in Figure 13.12 365
13.14 Original multitone image ”Ramp” (X) 369
13.15 Secret pattern ”Column” to be embedded in the halftone image (W) 369
13.16 Halftone images generated by error diffusion with the Jarvis kernel (Y1) 370
13.17 DHCED-generated Y2 (T = 10) of Ramp with respect to X in Figure 13.14, W in Figure 13.15, and Y1 in Figure 13.16. 370
13.18 Image Y obtained by overlaying Y1 in Figure 13.16 and Y2 in Figure 13.17. 371
13.19 Row-wise average intensity of Wb in Y in Figure 13.18 vs rowwise average intensity of X in Figure 13.14 (Ramp) 372
13.20 Row-wise Δintensity of Y in Figure 13.18 vs row-wise average intensity of X in Figure 13.14 (Ramp) 372
13.21 Contrast of Y in Figure 13.18 vs row-wise average intensity of X in Figure 13.14 (Ramp) 373
13.22 Row-wise average intensity of Y1 in Figure 13.4 and Y2 in Figure 13.9 vs row-wise average intensity of X in Figure 13.14 (Ramp) 373
13.23 DHSED-generated Y2 (L = 5) of Ramp with respect to X in Figure 13.14, W in Figure 13.15 and Y1 in Figure 13.16 375
13.24 Image Y obtained by overlaying Y1 in Figure 13.16 and Y2 in Figure 13.23. 375
13.25 Row-wise average intensity of Wb in Y in Figure 13.24 vs rowwise average intensity of X in Figure 13.14 (Ramp) 376
13.26 Row-wise Δintensity of Y in Figure 13.24 vs row-wise average intensity of X in Figure 13.14 (Ramp) 376
13.27 Contrast of Y in Figure 13.24 vs row-wise average intensity of X in Figure 13.14 (Ramp) 377
13.28 Row-wise average intensity Y1 in Figure 13.4 and Y2 in Figure 13.23 vs row-wise average intensity of X in Figure 13.14 (Ramp) 378
13.29 Theoretical average local intensity of Wb in Y for DHSED and DHCED vs row-wise average intensity of X in Figure 13.14 (Ramp) 378
13.30 Theoretical contrast of Y for DHSED and DHCED vs rowwise average intensity of X in Figure 13.14 (Ramp). 379
14.1 Principle of image sharing 383
14.2 Image sharing based on the Lagrange interpolation in (a) and (b) 390
14.3 Experimental results of image sharing based on the Lagrange interpolation in (a) and (b) 391
14.4 The image sharing by using a high degree polynomial interpolation in (a)-(c) 392
14.5 Intersection of two pencils of lines in (a) and (b) 394
14.6 Image sharing scheme based on moving lines 395
14.7 Improved algorithm of image sharing 397
14.8 The experimental results of image sharing by moving lines 397
14.9 The experimental results of image sharing by moving lines 398
14.10 The experimental results of image sharing by moving lines 398
14.11 Breaking the correlation of neighboring blocks in an image 399
15.1 The format of Bij, where xj, wj, υi, and υi are represented as binary pattern 408
15.2 The format of stego-block with the size of 2 × 2 gray-level pixels 409
15.3 Stego-block used in Yang et al. which is revised from Figure 15.2, where hash is used in the pixel of ŵi = (wj1, ⋯, wi5, hi, yi3, yi4) 409
15.4 Demonstration of steps in RAHA 414
15.5 A secret sharing system with target secret embedding of high capacity and detection authentication: (a) Flowchart of target secret embedding procedures; (b) Recovery of target secret forms the stego-images in our secret sharing systems 417
15.6 (a) the target secret images; (b)–(e) the four cover-images; (b′)–(e′) the four stego-images 420
15.7 (a) and (b) the target secret images; (c)–(h) the four coverimages; (c′)–(h′) the four stego-images 420
15.8 (a) the target images; (b)–(e) the four cover images; (b′)–(e′) the four stego-images 421
15.9 Minor bit adjustments in the stego-image of ”airplane.” (a) Lin-Tsai scheme, (b) Yang et al. scheme, and (c) our scheme 421
15.10 Partial area adjustments in the stego-images of ”sailboat.” (a) Lin-Tsai scheme, (b) Yang et al.’s scheme, and (c) our scheme 422
15.11 Replacement of ”airplane” stego-image with ”pepper.” (a) original stego-image of ”Airplane”, (b) replaced by ”pepper” Lin-Tsai scheme, (c) replaced by ”pepper” in Yang et al.’s scheme, and (c) detected in our scheme 422
16.1 The ij-th block of the k-th cover 429
16.2 The block of the k-th stego-image in Lin-Tsai’s scheme 430
16.3 The cover blocks used in Yang et al.’s scheme 431
16.4 The block of a stego-image in Yang et al.’s scheme 431
16.5 The block of a stego-image in Chang et al.’s scheme 433
16.6 The flowchart of Chang et al.’s scheme 434
16.7 Error diffusion architecture 435
16.8 The kernel weights of Floyd and Steinberg’s error filter 435
16.9 The positions of pixels located at the border in an image 436
16.10 The “excursion” skill 437
16.11 The neighboring pixels that accepted error diffusion for Case 1 438
16.12 The neighboring pixels that accepted error diffusion for Case 2 438
16.13 The neighboring pixels that accepted error diffusion for Case 3 439
16.14 Example of sampling an image: (a) Real signal R; (b) Sampled signal D of R; (c) Sampled signal D’ of D 439
16.15 The flowchart of Chung and Wu’s ELUT scheme 441
16.16 Procedure for generating final grayscale image in Step 4 443
16.17 The flowchart of the work by the sender 446
16.18 The flowchart of the work by the recipient 446
16.19 The z-th block of GI and the corresponding HIz, Pz 447
16.20 The four pixels of each cover block CBi 448
16.21 Hiding the six data bits of F(Xi) 448
16.22 Hiding the check bits p1, p2 449
16.23 The flowchart of Step 4 450
16.24 The four pixels of each stego block CB′j 451
16.25 The 2-bit check bits carried in CB′z when t =2 451
16.26 The bits of Xi and F(Xi) carried in the stego block 452
16.27 The test images 454
16.28 The experimental results for comparing the PSNR among the past work and ours 455
16.29 The visual quality of the reconstructed grayscale image 456
16.30 Three tampered stego-images 457
17.1 A (2, 2)-VCS of h = 1, l = 0, and m = 2: (a) the secret image (b) and (c) two shadows (d) the reconstructed image 467
17.2 A (2, 2)-GVCS of h = 1, l = 0, and m = 2: (a) and (b) two shadows (c) the reconstructed image 472
17.3 A (2, 2)-PISSS: (a) 512 × 512 gray-level Lena secret image (b) and (c) 512 × 256 gray-level noise-like shadows 475
17.4 The proposed (2, 2)-TiOISSS using base matrices with h = 1, l = 0, and m = 2: (a) 512 × 256 halftone image (b) and (c) two 512 × 512 gray-and-white shadows (d) the previewed image 476
17.5 The proposed (2, 2)-TiOISSS using base matrices with h = 1, l = 0, and m = 3: (a) and (b) two 512 × 512 gray-and-white shadows (c) the previewed image 477