Tampered Image Recognition Algorithm Based on Progressive Hybrid Feature

Table 1. Type of geometric attack in MICC-F220 dataset
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Table 1. Type of geometric attack in MICC-F220 dataset
Parameter G1 G2 G3 G4 G5 G6 G7 G8 G9 G10
$θ$ /（°） 0 10 20 30 40 0 0 0 10 20
L_x 1 1 1 1 1 1.2 1.3 1.4 1.2 1.4
L_y 1 1 1 1 1 1.2 1，3 1.4 1.2 1.4

Table 2. Type of geometric attack in MICC-F2000 dataset
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Table 2. Type of geometric attack in MICC-F2000 dataset
Parameter G1 G2 G3 G4 G5 G6 G7 G8 G9 G10 G11 G12 G13 G14
$θ$ /（°） 0 5 25 70 90 0 0 0 0 0 0 0 40 30
L_x 1 1 1 1 1 1.2 1.5 2.0 0.7 0.5 1.4 2.6 3.4 1.4
L_y 1 1 1 1 1 1.2 1，5 2.0 0.7 0.5 1.7 1.3 1.2 0.7

Table 3. Attack type
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Table 3. Attack type
Dataset a b c d
MICC-F220 G1 G2，G3，G4，G5 G6，G7，G8 G9，G10
MICC-F2000 G1 G2，G3，G4，G5 G6，G7，G8，G9，G10，G11，G12 G13，G14

Table 4. Experimental results of each stage
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Table 4. Experimental results of each stage
Algorithm TPR /% FPR /% F1 /%
Soni 97.5 8.5 94.7
Non-threshold method 98.2 9.09 94.6
Non-threshold method+hybrid feature 98.2 8.1 95.1

Table 5. Comparison of running time
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Table 5. Comparison of running time
Algorithm Time /s
Silva^［17］ 39
Pun^［19］ 399
Pun^［27］ 123
Ryu^［6］ 565
Soni^［21］ 38
Proposed algorithm 47

Table 6. Performance comparison between proposed algorithm and CKN algorithm
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Table 6. Performance comparison between proposed algorithm and CKN algorithm
Algorithm TPR /% FPR /% F1 /%
CKN 93 11 87.2
Proposed algorithm 97.2 6.4 92.9

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Yihang Peng, Wujian Ye, Yijun Liu. Tampered Image Recognition Algorithm Based on Progressive Hybrid Feature[J]. Laser & Optoelectronics Progress, 2022, 59(2): 0211001

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