Research Article
A Robust Coverless Image Steganography Algorithm Based on Image Retrieval with SURF Features
Table 5
Robustness comparison with LDA_DCT [
18], DenseNet_DWT [
19], and DCMH-CNN [
32] in ImageNet dataset.
| | Processing | Size | LDA_DCT (%) | DenseNet_DWT (%) | DCMH-CNN (%) | Proposed (%) |
| | JPEG | Q (10) | 91.4 | 98.0 | 59.4 | 98.8 | | Q (50) | 98.4 | 98.0 | 94.1 | 100.0 | | Q (90) | 99.6 | 100.0 | 100.0 | 100.0 |
| | Gauss-N | σ (0.001) | 94.1 | 98.8 | 99.6 | 100.0 | | σ (0.005) | 94.1 | 98.0 | 93.0 | 100.0 |
| | S&P-N | σ (0.001) | 98.4 | 100.0 | 100.0 | 100.0 | | σ (0.005) | 94.1 | 98.8 | 99.6 | 100.0 |
| | Speckle-N | σ (0.01) | 99.6 | 99.2 | 99.6 | 99.6 | | σ (0.05) | 89.8 | 91.0 | 73.8 | 98.4 |
| | Gauss-F | (33) | 99.2 | 100.0 | 100.0 | 100.0 |
| | Mean-F | (33) | 98.8 | 100.0 | 97.7 | 100.0 |
| | Median-F | (33) | 94.5 | 95.7 | 98.8 | 100.0 |
| | Centered-C | 20% | 66.8 | 20.3 | 98.4 | 94.5 | | 50% | 11.3 | 3.5 | 66.0 | 48.0 |
| | Edge-C | 10% | 18.8 | 55.5 | 97.3 | 100.0 | | 20% | 6.3 | 28.5 | 90.6 | 92.6 |
| | Rotation | 10° | 66.4 | 36.7 | 100.0 | 98.8 | | 30° | 8.2 | 5.9 | 93.8 | 94.1 | | 50° | 5.1 | 2.3 | 70.3 | 95.7 |
| | Translation | (80, 50) | 21.1 | 36.7 | 98.4 | 98.8 | | (160, 100) | 8.6 | 9.0 | 88.3 | 94.1 | | (320, 200) | 6.3 | 5.9 | 70.3 | 91.8 |
| | Scaling | 0.5 | 97.7 | 92.2 | 87.5 | 98.4 | | 0.75 | 96.9 | 94.9 | 100.0 | 100.0 | | 1.5 | 99.2 | 98.8 | 100.0 | 100.0 | | 3 | 98.8 | 100.0 | 100.0 | 100.0 |
| | C-H-E | | 73.4 | 71.1 | 96.5 | 75.0 | | Gamma-C | 0.8 | 89.8 | 94.5 | 100.0 | 100.0 |
| | Average | | 68.8 | 69.0 | 91.2 | 95.7 |
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The bold data in the table represent the highest accuracy among the compared algorithms. The italicized data represent the second-highest accuracy.
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