• Laser & Optoelectronics Progress
  • Vol. 58, Issue 20, 2010017 (2021)
Sen Hu1, Deyang Wu2、*, Meiyu Zhong2, Miaomiao Wang1, Jing Zhao2、**, Yong Tang2, and Changbo Qu1、***
Author Affiliations
  • 1College of Software, Liaoning Technical University, Huludao, Liaoning, 125105, China
  • 2College of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei, 0 66004, China
  • show less
    DOI: 10.3788/LOP202158.2010017 Cite this Article Set citation alerts
    Sen Hu, Deyang Wu, Meiyu Zhong, Miaomiao Wang, Jing Zhao, Yong Tang, Changbo Qu. Color Zero-Watermarking Algorithm Based on SURF and Halftone Mapping Encryption[J]. Laser & Optoelectronics Progress, 2021, 58(20): 2010017 Copy Citation Text show less
    Comparison of feature points before and after screening. (a) Feature point overlap; (b) correction results with large error; (c) extraction results of error correction; (d) filtered feature point matching; (e) corrected image; (f) correctly corrected extraction results
    Fig. 1. Comparison of feature points before and after screening. (a) Feature point overlap; (b) correction results with large error; (c) extraction results of error correction; (d) filtered feature point matching; (e) corrected image; (f) correctly corrected extraction results
    Comparison of encryption image and original image under different keys. (a) (b) (e) Encryption results with the same key and different initial offset values; (c) (d) encryption results with different keys; (f) original image
    Fig. 2. Comparison of encryption image and original image under different keys. (a) (b) (e) Encryption results with the same key and different initial offset values; (c) (d) encryption results with different keys; (f) original image
    Halftone decryption results. (a)(e) Encryption and decryption images of R channel; (b)(f) encryption and decryption images of G channel; (c)(g) encryption and decryption images of B channel; (d)(h) encryption and decryption images after channel fusion
    Fig. 3. Halftone decryption results. (a)(e) Encryption and decryption images of R channel; (b)(f) encryption and decryption images of G channel; (c)(g) encryption and decryption images of B channel; (d)(h) encryption and decryption images after channel fusion
    Extraction results under different key conditions. (a) Sub-block segmentation key has error in R channel; (b) sub-block segmentation key has error in R and G channels; (c) sub-block segmentation key has error in R, B and G channels; (d) initial key has error in R channel; (e) initial key has error in R and G channels; (f) initial key has error in R, B and G channels; (g) sub-block segmentation key has error in R channel and initial key has error in R and G channels; (h) sub-block segmentation key has error in R and G channels and initial key has error in R channel; (i) sub-block segmentation key and initial key has in R, B and G channels
    Fig. 4. Extraction results under different key conditions. (a) Sub-block segmentation key has error in R channel; (b) sub-block segmentation key has error in R and G channels; (c) sub-block segmentation key has error in R, B and G channels; (d) initial key has error in R channel; (e) initial key has error in R and G channels; (f) initial key has error in R, B and G channels; (g) sub-block segmentation key has error in R channel and initial key has error in R and G channels; (h) sub-block segmentation key has error in R and G channels and initial key has error in R channel; (i) sub-block segmentation key and initial key has in R, B and G channels
    Zero watermark generation and copyright logo extraction
    Fig. 5. Zero watermark generation and copyright logo extraction
    Host images and logo images. (a) Baboon; (b) car; (c) Lena; (d) pepper; (e) plane; (f) sailboat; (g) logo
    Fig. 6. Host images and logo images. (a) Baboon; (b) car; (c) Lena; (d) pepper; (e) plane; (f) sailboat; (g) logo
    Lena graph and detection results under non geometric attacks. (a) Gaussian noise (0.05); (b) salt-and-peppers noise (0.05); (c) median filtering (7×7); (d) JPEG compression(10%)
    Fig. 7. Lena graph and detection results under non geometric attacks. (a) Gaussian noise (0.05); (b) salt-and-peppers noise (0.05); (c) median filtering (7×7); (d) JPEG compression(10%)
    Geometric correction results and copyright logo. (a)(h) rotate 25°; (b)(i) rotate 50°; (c)(j) rotate 75°; (d)(k) rotate 100°; (e)(l) rotate 125°; (f)(m) rotate 150°; (g)(n) rotate 175°
    Fig. 8. Geometric correction results and copyright logo. (a)(h) rotate 25°; (b)(i) rotate 50°; (c)(j) rotate 75°; (d)(k) rotate 100°; (e)(l) rotate 125°; (f)(m) rotate 150°; (g)(n) rotate 175°
    Comparative experiment results. (a) Gaussian filtering; (b) salt-and-peppers noise; (c) JPEG compression; (d) median filtering; (e) Gaussian filtering; (f) rotation attack; (g) translation attack; (h) scaling attack
    Fig. 9. Comparative experiment results. (a) Gaussian filtering; (b) salt-and-peppers noise; (c) JPEG compression; (d) median filtering; (e) Gaussian filtering; (f) rotation attack; (g) translation attack; (h) scaling attack
    Logo imageFalse alarm rate of input image
    BaboonCarLenaPepperPlaneSailboat
    Baboon1.00000.56020.56400.56720.59250.5558
    Car0.55851.00000.57310.55800.48100.5585
    Lena0.56970.56371.00000.56710.57290.5604
    Pepper0.56050.55880.56361.00000.53290.5605
    Plane0.56500.60080.56690.55371.00000.5909
    Sailboat0.58850.55260.55730.58570.53241.0000
    Table 1. Experimental results of false alarm rate
    Attack typeParameterBaboonCarLenaPepperPlaneSailboat
    Gaussian noise0.020.98870.98770.98600.99000.99060.9948
    0.050.98200.98010.97800.98330.98490.9925
    Salt &pepperNoise0.020.99350.99360.99240.99460.99450.9974
    0.050.98960.98880.98900.99230.99120.9956
    Speckle noise0.020.99390.99140.99310.99570.99260.9975
    0.050.98830.98510.98810.99330.98890.9952
    Median filtering3×30.99490.99640.99820.99810.99750.9984
    7×70.98900.98970.99300.99550.99050.9947
    Wiener filtering3×30.99860.99880.99920.99920.99900.9994
    7×70.99530.99470.99650.99690.99640.9978
    Low pass filtering3×30.99840.99860.99820.99850.99830.9991
    7×70.99760.99770.99750.99800.99740.9986
    JPEG compression100.98100.98000.97570.98440.98320.9910
    500.99550.99470.99470.99540.99600.9978
    Table 2. Experimental results of non geometric attack (NC)
    Attack typeParameterBaboonCarLenaPepperPlaneSailboat
    Rotation1.00001.00001.00001.00001.00001.0000
    25°0.88260.80770.86670.87170.82370.9359
    50°0.84770.76790.84890.85680.81170.9170
    75°0.90910.86080.90880.91480.83260.9464
    100°0.94350.90440.93360.93610.92120.9606
    125°0.86150.77800.84690.85560.81030.9220
    150°0.81670.78760.85660.87160.82350.9199
    175°0.95960.95150.97250.97250.95990.9845
    Move5 lines and 5 columns0.99370.98990.99060.99240.98230.9961
    10 lines and 20 columns0.97930.96430.97550.97890.96440.9875
    Scaling0.250.99450.99430.99740.99720.99120.9974
    1.250.99970.99980.99990.99980.99910.9999
    Table 3. Experimental results of geometric attack (NC)
    StepTime /s
    Copyright watermark preprocessing0.1821
    Generate zero watermark0.5643
    Original image0.6009
    20° rotation0.6026
    45° rotation0.6241
    Salt-and-pepper noise 0.080.6344
    Wiener filter 9×90.6089
    Table 4. Run time test table
    Sen Hu, Deyang Wu, Meiyu Zhong, Miaomiao Wang, Jing Zhao, Yong Tang, Changbo Qu. Color Zero-Watermarking Algorithm Based on SURF and Halftone Mapping Encryption[J]. Laser & Optoelectronics Progress, 2021, 58(20): 2010017
    Download Citation