Table 19 Comparison of BER values between the proposed and existing methods13,43,44,47,48,45,46 under various attacks.
From: Robust zero-watermarking for color images using hybrid deep learning models and encryption
Attacks | BER | |||||||
---|---|---|---|---|---|---|---|---|
Suggested algorithm | ||||||||
Gaussian noise (0.1) | 0 | 0.0002 | 0.0034 | 0.001 | 0.0010 | 0.01 | 0.0082 | – |
Gaussian noise (0.3) | 0 | 0 | 0.0084 | 0.0026 | 0.0010 | 0.0106 | 0.0092 | – |
Gaussian noise (0.5) | 0 | 0.0002 | 0.0093 | 0.0036 | 0.0010 | 0.0121 | 0.0102 | – |
Gaussian noise (0.01) | 0 | 0 | 0.0323 | 0.0091 | – | 0.0296 | 0.0421 | 0.0172 |
Salt & Pepper noise (0.01) | 0 | 0 | 0.0125 | 0.0091 | – | 0.0421 | 0.0926 | 0.0091 |
Salt & Pepper noise (0.03) | 0.0005 | – | 0.0290 | 0.0124 | 0.0010 | 0.0542 | 0.116 | – |
JPEG compression (F = 10) | 0 | 0.0002 | 0.0253 | 0.0041 | 0 | 0.1231 | 0.4844 | – |
JPEG compression (F = 30) | 0 | 0 | 0.0135 | 0.0037 | – | 0.0983 | 0.4063 | 0.0131 |
JPEG compression (F = 50) | 0 | 0 | 0.0111 | 0.0021 | 0 | 0.0849 | 0.3438 | 0.0099 |
JPEG compression (F = 70) | 0 | 0 | 0.0039 | 0.0007 | 0.0005 | 0.0183 | 0.0713 | 0.0058 |
JPEG compression (F = 90) | 0 | 0 | 0.0018 | 0.0002 | 0.0002 | 0.0073 | 0.0213 | – |
Average filter (3 × 3) | 0 | 0 | 0.0099 | 0.202 | 0.0001 | 0.0029 | 0.099 | 0.0079 |
Average filter (5 × 5) | 0 | 0.0002 | 0.0181 | 0.0361 | 0.0001 | 0.298 | 0.0455 | 0.0157 |
Average filter (7 × 7) | 0 | 0.0009 | 0.0245 | 0.0618 | 0.0001 | 0.2919 | 0.0630 | – |
Median filter (3 × 3) | 0.0005 | 0.0002 | 0.0068 | 0.001 | 0 | 0.0039 | 0.0442 | 0.0064 |
Median filter (5 × 5) | 0 | 0 | 0.0135 | 0.009 | 0.0007 | 0.02866 | 0.0505 | 0.0099 |
Median filter (7 × 7) | 0 | 0.0002 | 0.0195 | 0.011 | 0.0001 | 0.02910 | 0.0984 | – |
Rotation (3°) | 0.0005 | 0 | – | 0.00959 | 0.0002 | 0 | – | 0.1333 |
Rotation (5°) | 0 | 0 | – | 0.02982 | 0.0002 | 0 | – | 0.1858 |
Scaling (0.5) | 0 | 0 | – | 0.00659 | 0.0002 | 0 | – | 0.0071 |
Sharpening | 0 | 0 | 0.0007 | 0 | 0.0001 | 0.00018 | 0.0009 | – |