电子学报 ›› 2022, Vol. 50 ›› Issue (8): 1840-1850.DOI: 10.12263/DZXB.20211428
王波1, 王悦1, 王伟2, 侯嘉尧1
收稿日期:
2021-10-19
修回日期:
2022-02-09
出版日期:
2022-08-25
通讯作者:
作者简介:
基金资助:
WANG Bo1, WANG Yue1, WANG Wei2, HOU Jia-yao1
Received:
2021-10-19
Revised:
2022-02-09
Online:
2022-08-25
Published:
2022-09-08
Corresponding author:
摘要:
针对相机来源取证中的开放环境问题,本文提出一种自适应聚类优化包络的相机来源取证方法,解决了现有方法在训练相机模型数量少的恶劣情况下检测精度低的问题.首先,通过手肘法得到每一类相机数据的聚类个数,并以该聚类数为参照进行
中图分类号:
王波, 王悦, 王伟, 侯嘉尧. 开放环境下自适应聚类优化包络的相机来源取证[J]. 电子学报, 2022, 50(8): 1840-1850.
WANG Bo, WANG Yue, WANG Wei, HOU Jia-yao. Envelope Optimization Based on Adaptive Clustering for Open-Set Camera Model Identification[J]. Acta Electronica Sinica, 2022, 50(8): 1840-1850.
相机模型 | 缩写 | 数量 | 尺寸 |
---|---|---|---|
Kodak_M1063 | K1 | 2 391 | 3 664×2 748 |
Olympus_mju_1050SW | O1 | 1 037 | 3 648×2 736 |
Praktica_DCZ5_9 | P1 | 1 019 | 2 560×1 920 |
Panasonic_DMC-FZ50 | Pa1 | 931 | 3 648×2 736 |
Casio_EX-Z150 | C1 | 925 | 3 264×2 448 |
Nikon_CoolPixS710 | N1 | 925 | 4 352×3 264 |
Ricoh_GX100 | R1 | 854 | 3 648×2 736 |
Nikon_D200 | N2 | 752 | 3 872×2 592 |
Sony_DSC-T77 | S1 | 725 | 3 648×2 736 |
Samsung_L74wide | Sa1 | 686 | 3 072×2 304 |
表1 Dresden数据集中选择的相机模型信息
相机模型 | 缩写 | 数量 | 尺寸 |
---|---|---|---|
Kodak_M1063 | K1 | 2 391 | 3 664×2 748 |
Olympus_mju_1050SW | O1 | 1 037 | 3 648×2 736 |
Praktica_DCZ5_9 | P1 | 1 019 | 2 560×1 920 |
Panasonic_DMC-FZ50 | Pa1 | 931 | 3 648×2 736 |
Casio_EX-Z150 | C1 | 925 | 3 264×2 448 |
Nikon_CoolPixS710 | N1 | 925 | 4 352×3 264 |
Ricoh_GX100 | R1 | 854 | 3 648×2 736 |
Nikon_D200 | N2 | 752 | 3 872×2 592 |
Sony_DSC-T77 | S1 | 725 | 3 648×2 736 |
Samsung_L74wide | Sa1 | 686 | 3 072×2 304 |
相机模型 | 缩写 | 数量 | 尺寸 |
---|---|---|---|
Apple iPhone 5s | A1 | 180 | 3 264×2 488 |
Apple iPhone 6 | A2 | 180 | 3 264×2 488 |
Apple iPhone 6s | A3 | 180 | 4 032×3 024 |
Apple iPhone 7 | A4 | 180 | 4 032×3 024 |
Asus Zenfone 2 | AZ1 | 180 | 4 096×3 072 |
LG G3 | L1 | 180 | 4 160×2 340 |
Motoroal Moto G | M1 | 180 | 3 264×1 836 |
Samsung Galaxy A3 | S1 | 180 | 4 128×2 322 |
Samsung Galaxy S5 | S2 | 180 | 5 312×2 988 |
Samsung Galaxy S7 Edge | S3 | 180 | 4 032×3 024 |
表2 SOCRatES数据集中选择的相机模型信息
相机模型 | 缩写 | 数量 | 尺寸 |
---|---|---|---|
Apple iPhone 5s | A1 | 180 | 3 264×2 488 |
Apple iPhone 6 | A2 | 180 | 3 264×2 488 |
Apple iPhone 6s | A3 | 180 | 4 032×3 024 |
Apple iPhone 7 | A4 | 180 | 4 032×3 024 |
Asus Zenfone 2 | AZ1 | 180 | 4 096×3 072 |
LG G3 | L1 | 180 | 4 160×2 340 |
Motoroal Moto G | M1 | 180 | 3 264×1 836 |
Samsung Galaxy A3 | S1 | 180 | 4 128×2 322 |
Samsung Galaxy S5 | S2 | 180 | 5 312×2 988 |
Samsung Galaxy S7 Edge | S3 | 180 | 4 032×3 024 |
Dresden | SOCRatES | ||
---|---|---|---|
相机模型 | 个数 | 相机模型 | 个数 |
K1 | 2 | A1 | 1 |
O1 | 2 | A2 | 1 |
P1 | 3 | A3 | 1 |
Pa1 | 2 | A4 | 2 |
C1 | 2 | AZ1 | 1 |
N1 | 2 | L1 | 1 |
R1 | 1 | M1 | 2 |
N2 | 2 | S1 | 1 |
S1 | 2 | S2 | 1 |
Sa1 | 2 | S3 | 2 |
表3 Dresden与SOCRatES中聚类子类个数 (个)
Dresden | SOCRatES | ||
---|---|---|---|
相机模型 | 个数 | 相机模型 | 个数 |
K1 | 2 | A1 | 1 |
O1 | 2 | A2 | 1 |
P1 | 3 | A3 | 1 |
Pa1 | 2 | A4 | 2 |
C1 | 2 | AZ1 | 1 |
N1 | 2 | L1 | 1 |
R1 | 1 | M1 | 2 |
N2 | 2 | S1 | 1 |
S1 | 2 | S2 | 1 |
Sa1 | 2 | S3 | 2 |
相机模型 | 算法 | ||||
---|---|---|---|---|---|
SCIU | CCF | CCF_AC | SC | 本文算法 | |
K1 | 52.0 | 51.1 | 60.2 | 93.2 | 94.4 |
O1 | 48.3 | 42.8 | 47.3 | 87.9 | 95.1 |
P1 | 44.0 | 45.1 | 50.6 | 86.0 | 91.2 |
Pa1 | 36.3 | 44.8 | 52.5 | 93.0 | 98.2 |
C1 | 67.4 | 45.8 | 51.7 | 93.1 | 94.1 |
N1 | 34.1 | 43.1 | 53.5 | 86.6 | 89.9 |
R1 | 76.6 | 50.8 | 50.8 | 100.0 | 100.0 |
N2 | 23.3 | 51.9 | 53.5 | 90.1 | 96.3 |
S1 | 34.1 | 42.1 | 56.7 | 97.1 | 98.4 |
Sa1 | 12.8 | 47.2 | 56.1 | 88.2 | 94.1 |
AVG | 42.9 | 46.5 | 53.3 | 91.5 | 95.2 |
表4 Dresden已知来源相机模型识别精度 (%)
相机模型 | 算法 | ||||
---|---|---|---|---|---|
SCIU | CCF | CCF_AC | SC | 本文算法 | |
K1 | 52.0 | 51.1 | 60.2 | 93.2 | 94.4 |
O1 | 48.3 | 42.8 | 47.3 | 87.9 | 95.1 |
P1 | 44.0 | 45.1 | 50.6 | 86.0 | 91.2 |
Pa1 | 36.3 | 44.8 | 52.5 | 93.0 | 98.2 |
C1 | 67.4 | 45.8 | 51.7 | 93.1 | 94.1 |
N1 | 34.1 | 43.1 | 53.5 | 86.6 | 89.9 |
R1 | 76.6 | 50.8 | 50.8 | 100.0 | 100.0 |
N2 | 23.3 | 51.9 | 53.5 | 90.1 | 96.3 |
S1 | 34.1 | 42.1 | 56.7 | 97.1 | 98.4 |
Sa1 | 12.8 | 47.2 | 56.1 | 88.2 | 94.1 |
AVG | 42.9 | 46.5 | 53.3 | 91.5 | 95.2 |
相机模型 | 算法 | ||||
---|---|---|---|---|---|
SCIU | CCF | CCF_AC | SC | 本文算法 | |
K1 | 78.3 | 85.6 | 92.7 | 84.1 | 87.2 |
O1 | 80.0 | 95.0 | 100.0 | 97.4 | 97.6 |
P1 | 75.6 | 97.1 | 96.2 | 94.9 | 95.8 |
Pa1 | 84.2 | 91.4 | 93.9 | 97.1 | 96.9 |
C1 | 87.5 | 99.6 | 99.6 | 94.4 | 96.4 |
N1 | 93.5 | 98.1 | 97.8 | 96.9 | 97.0 |
R1 | 81.8 | 99.0 | 99.0 | 98.8 | 98.8 |
N2 | 85.3 | 100.0 | 100.0 | 99.8 | 99.8 |
S1 | 92.0 | 93.9 | 94.0 | 95.4 | 96.9 |
Sa1 | 89.5 | 98.0 | 98.0 | 94.6 | 95.1 |
AVG | 84.8 | 95.8 | 97.1 | 95.3 | 96.1 |
表5 Dresden未知来源相机模型识别精度 (%)
相机模型 | 算法 | ||||
---|---|---|---|---|---|
SCIU | CCF | CCF_AC | SC | 本文算法 | |
K1 | 78.3 | 85.6 | 92.7 | 84.1 | 87.2 |
O1 | 80.0 | 95.0 | 100.0 | 97.4 | 97.6 |
P1 | 75.6 | 97.1 | 96.2 | 94.9 | 95.8 |
Pa1 | 84.2 | 91.4 | 93.9 | 97.1 | 96.9 |
C1 | 87.5 | 99.6 | 99.6 | 94.4 | 96.4 |
N1 | 93.5 | 98.1 | 97.8 | 96.9 | 97.0 |
R1 | 81.8 | 99.0 | 99.0 | 98.8 | 98.8 |
N2 | 85.3 | 100.0 | 100.0 | 99.8 | 99.8 |
S1 | 92.0 | 93.9 | 94.0 | 95.4 | 96.9 |
Sa1 | 89.5 | 98.0 | 98.0 | 94.6 | 95.1 |
AVG | 84.8 | 95.8 | 97.1 | 95.3 | 96.1 |
相机模型 | 算法 | ||||
---|---|---|---|---|---|
SCIU | CCF | CCF_AC | SC | 本文算法 | |
K1 | 72.2 | 77.5 | 85.0 | 86.2 | 88.8 |
O1 | 76.8 | 89.6 | 94.6 | 96.4 | 97.3 |
P1 | 72.4 | 91.9 | 91.6 | 94.0 | 95.3 |
Pa1 | 79.8 | 87.1 | 90.1 | 96.7 | 97.0 |
C1 | 85.6 | 94.6 | 95.2 | 94.3 | 96.2 |
N1 | 88.1 | 93.1 | 93.7 | 95.9 | 96.3 |
R1 | 81.3 | 94.9 | 94.9 | 98.9 | 98.9 |
N2 | 80.7 | 96.4 | 96.6 | 99.1 | 99.5 |
S1 | 87.9 | 90.2 | 91.3 | 95.6 | 97.0 |
Sa1 | 84.3 | 94.6 | 95.2 | 94.1 | 95.0 |
AVG | 80.9 | 91.0 | 92.8 | 95.1 | 96.1 |
表6 Dresden整体相机模型识别精度 (%)
相机模型 | 算法 | ||||
---|---|---|---|---|---|
SCIU | CCF | CCF_AC | SC | 本文算法 | |
K1 | 72.2 | 77.5 | 85.0 | 86.2 | 88.8 |
O1 | 76.8 | 89.6 | 94.6 | 96.4 | 97.3 |
P1 | 72.4 | 91.9 | 91.6 | 94.0 | 95.3 |
Pa1 | 79.8 | 87.1 | 90.1 | 96.7 | 97.0 |
C1 | 85.6 | 94.6 | 95.2 | 94.3 | 96.2 |
N1 | 88.1 | 93.1 | 93.7 | 95.9 | 96.3 |
R1 | 81.3 | 94.9 | 94.9 | 98.9 | 98.9 |
N2 | 80.7 | 96.4 | 96.6 | 99.1 | 99.5 |
S1 | 87.9 | 90.2 | 91.3 | 95.6 | 97.0 |
Sa1 | 84.3 | 94.6 | 95.2 | 94.1 | 95.0 |
AVG | 80.9 | 91.0 | 92.8 | 95.1 | 96.1 |
相机模型 | 算法 | ||||
---|---|---|---|---|---|
SCIU | CCF | CCF_AC | SC | 本文算法 | |
A1 | 21.2 | 52.2 | 52.2 | 54.1 | 54.1 |
A2 | 34.1 | 54.8 | 54.8 | 68.0 | 68.0 |
A3 | 13.5 | 46.8 | 46.8 | 74.2 | 74.2 |
A4 | 56.8 | 51.6 | 64.0 | 63.0 | 87.0 |
AZ1 | 24.9 | 54.3 | 54.3 | 80.8 | 80.8 |
L1 | 35.7 | 47.3 | 47.3 | 68.2 | 68.2 |
M1 | 27.7 | 49.4 | 76.0 | 62.5 | 77.0 |
S1 | 29.3 | 56.0 | 56.0 | 63.0 | 63.0 |
S2 | 37.6 | 52.8 | 52.8 | 74.4 | 74.4 |
S3 | 21.3 | 54.1 | 66.0 | 64.8 | 79.9 |
AVG | 30.2 | 51.9 | 57.0 | 67.3 | 72.7 |
表7 SOCRatES已知来源相机模型识别精度 (%)
相机模型 | 算法 | ||||
---|---|---|---|---|---|
SCIU | CCF | CCF_AC | SC | 本文算法 | |
A1 | 21.2 | 52.2 | 52.2 | 54.1 | 54.1 |
A2 | 34.1 | 54.8 | 54.8 | 68.0 | 68.0 |
A3 | 13.5 | 46.8 | 46.8 | 74.2 | 74.2 |
A4 | 56.8 | 51.6 | 64.0 | 63.0 | 87.0 |
AZ1 | 24.9 | 54.3 | 54.3 | 80.8 | 80.8 |
L1 | 35.7 | 47.3 | 47.3 | 68.2 | 68.2 |
M1 | 27.7 | 49.4 | 76.0 | 62.5 | 77.0 |
S1 | 29.3 | 56.0 | 56.0 | 63.0 | 63.0 |
S2 | 37.6 | 52.8 | 52.8 | 74.4 | 74.4 |
S3 | 21.3 | 54.1 | 66.0 | 64.8 | 79.9 |
AVG | 30.2 | 51.9 | 57.0 | 67.3 | 72.7 |
相机模型 | 算法 | ||||
---|---|---|---|---|---|
SCIU | CCF | CCF_AC | SC | 本文算法 | |
A1 | 99.7 | 78.2 | 78.2 | 98.1 | 98.1 |
A2 | 99.1 | 92.0 | 92.0 | 82.0 | 82.0 |
A3 | 79.1 | 96.1 | 96.1 | 86.2 | 86.2 |
A4 | 88.5 | 88.0 | 90.0 | 76.0 | 91.0 |
AZ1 | 69.4 | 78.2 | 78.2 | 88.4 | 88.4 |
L1 | 70.9 | 89.0 | 89.0 | 88.0 | 88.0 |
M1 | 87.3 | 91.4 | 91.5 | 87.0 | 89.1 |
S1 | 90.2 | 99.0 | 99.0 | 100.0 | 100.0 |
S2 | 78.7 | 89.2 | 89.2 | 81.0 | 81.0 |
S3 | 91.0 | 91.1 | 91.0 | 85.1 | 91.2 |
AVG | 85.4 | 89.2 | 89.4 | 87.2 | 89.5 |
表8 SOCRatES未知来源相机模型识别精度 (%)
相机模型 | 算法 | ||||
---|---|---|---|---|---|
SCIU | CCF | CCF_AC | SC | 本文算法 | |
A1 | 99.7 | 78.2 | 78.2 | 98.1 | 98.1 |
A2 | 99.1 | 92.0 | 92.0 | 82.0 | 82.0 |
A3 | 79.1 | 96.1 | 96.1 | 86.2 | 86.2 |
A4 | 88.5 | 88.0 | 90.0 | 76.0 | 91.0 |
AZ1 | 69.4 | 78.2 | 78.2 | 88.4 | 88.4 |
L1 | 70.9 | 89.0 | 89.0 | 88.0 | 88.0 |
M1 | 87.3 | 91.4 | 91.5 | 87.0 | 89.1 |
S1 | 90.2 | 99.0 | 99.0 | 100.0 | 100.0 |
S2 | 78.7 | 89.2 | 89.2 | 81.0 | 81.0 |
S3 | 91.0 | 91.1 | 91.0 | 85.1 | 91.2 |
AVG | 85.4 | 89.2 | 89.4 | 87.2 | 89.5 |
相机模型 | 算法 | ||||
---|---|---|---|---|---|
SCIU | CCF | CCF_AC | SC | 本文算法 | |
A1 | 91.9 | 75.6 | 75.6 | 93.7 | 93.7 |
A2 | 92.6 | 88.3 | 88.3 | 80.6 | 80.6 |
A3 | 72.6 | 91.2 | 91.2 | 85.0 | 85.0 |
A4 | 85.3 | 84.4 | 87.4 | 74.7 | 90.6 |
AZ1 | 65.0 | 76.8 | 75.8 | 87.6 | 87.6 |
L1 | 67.4 | 84.8 | 84.8 | 86.0 | 86.0 |
M1 | 81.3 | 87.2 | 90.9 | 84.6 | 87.9 |
S1 | 84.1 | 94.7 | 94.7 | 96.3 | 96.3 |
S2 | 74.6 | 85.6 | 85.6 | 80.3 | 80.3 |
S3 | 84.0 | 87.4 | 88.5 | 83.1 | 90.1 |
AVG | 79.9 | 85.5 | 86.3 | 85.2 | 87.8 |
表9 SOCRatES整体相机模型识别精度 (%)
相机模型 | 算法 | ||||
---|---|---|---|---|---|
SCIU | CCF | CCF_AC | SC | 本文算法 | |
A1 | 91.9 | 75.6 | 75.6 | 93.7 | 93.7 |
A2 | 92.6 | 88.3 | 88.3 | 80.6 | 80.6 |
A3 | 72.6 | 91.2 | 91.2 | 85.0 | 85.0 |
A4 | 85.3 | 84.4 | 87.4 | 74.7 | 90.6 |
AZ1 | 65.0 | 76.8 | 75.8 | 87.6 | 87.6 |
L1 | 67.4 | 84.8 | 84.8 | 86.0 | 86.0 |
M1 | 81.3 | 87.2 | 90.9 | 84.6 | 87.9 |
S1 | 84.1 | 94.7 | 94.7 | 96.3 | 96.3 |
S2 | 74.6 | 85.6 | 85.6 | 80.3 | 80.3 |
S3 | 84.0 | 87.4 | 88.5 | 83.1 | 90.1 |
AVG | 79.9 | 85.5 | 86.3 | 85.2 | 87.8 |
相机模型 | SCIU | CCF | CCF_AC | SC | 本文算法 |
---|---|---|---|---|---|
K1 | 18 703.8 | 948.2 | 375.2 | 11.2 | 8.1 |
O1 | 14 540.3 | 111.8 | 48.3 | 6.9 | 5.2 |
P1 | 13 957.0 | 103.1 | 57.6 | 9.0 | 5.3 |
Pa1 | 14 397.3 | 36.8 | 78.5 | 6.3 | 9.9 |
C1 | 16 347.3 | 95.8 | 34.7 | 6.2 | 9.8 |
N1 | 13 573.1 | 77.1 | 34.5 | 6.4 | 10.0 |
R1 | 16 283.2 | 72.8 | 72.8 | 6.3 | 6.3 |
N2 | 16 367.3 | 47.9 | 22.5 | 6.2 | 9.1 |
S1 | 12 847.1 | 45.1 | 24.7 | 6.0 | 9.4 |
Sa1 | 10 237.8 | 38.2 | 19.1 | 6.2 | 9.6 |
AVG | 14 725.4 | 157.7 | 76.8 | 7.1 | 8.3 |
表10 Dresden时间复杂度对比 (s)
相机模型 | SCIU | CCF | CCF_AC | SC | 本文算法 |
---|---|---|---|---|---|
K1 | 18 703.8 | 948.2 | 375.2 | 11.2 | 8.1 |
O1 | 14 540.3 | 111.8 | 48.3 | 6.9 | 5.2 |
P1 | 13 957.0 | 103.1 | 57.6 | 9.0 | 5.3 |
Pa1 | 14 397.3 | 36.8 | 78.5 | 6.3 | 9.9 |
C1 | 16 347.3 | 95.8 | 34.7 | 6.2 | 9.8 |
N1 | 13 573.1 | 77.1 | 34.5 | 6.4 | 10.0 |
R1 | 16 283.2 | 72.8 | 72.8 | 6.3 | 6.3 |
N2 | 16 367.3 | 47.9 | 22.5 | 6.2 | 9.1 |
S1 | 12 847.1 | 45.1 | 24.7 | 6.0 | 9.4 |
Sa1 | 10 237.8 | 38.2 | 19.1 | 6.2 | 9.6 |
AVG | 14 725.4 | 157.7 | 76.8 | 7.1 | 8.3 |
相机模型 | SCIU | CCF | CCF_AC | SC | 本文算法 |
---|---|---|---|---|---|
A1 | 8 162.7 | 397.0 | 397.0 | 9.2 | 9.2 |
A2 | 8 825.3 | 408.1 | 408.1 | 8.7 | 8.7 |
A3 | 8 901.7 | 414.8 | 414.8 | 9.6 | 9.6 |
A4 | 9 174.7 | 412.3 | 9.1 | 9.7 | 8.9 |
AZ1 | 9 145.6 | 441.3 | 441.3 | 8.7 | 8.7 |
L1 | 9 318.7 | 391.5 | 391.5 | 9.0 | 9.0 |
M1 | 9 134.9 | 413.5 | 11.4 | 9.8 | 8.5 |
S1 | 8 932.7 | 451.5 | 451.5 | 8.9 | 8.9 |
S2 | 8 143.7 | 419.5 | 419.5 | 8.8 | 8.8 |
S3 | 8 923.9 | 493.4 | 12.5 | 8.7 | 7. 9 |
AVG | 8 866.4 | 424.3 | 295.7 | 9.1 | 8.8 |
表11 SOCRatES时间复杂度对比 (s)
相机模型 | SCIU | CCF | CCF_AC | SC | 本文算法 |
---|---|---|---|---|---|
A1 | 8 162.7 | 397.0 | 397.0 | 9.2 | 9.2 |
A2 | 8 825.3 | 408.1 | 408.1 | 8.7 | 8.7 |
A3 | 8 901.7 | 414.8 | 414.8 | 9.6 | 9.6 |
A4 | 9 174.7 | 412.3 | 9.1 | 9.7 | 8.9 |
AZ1 | 9 145.6 | 441.3 | 441.3 | 8.7 | 8.7 |
L1 | 9 318.7 | 391.5 | 391.5 | 9.0 | 9.0 |
M1 | 9 134.9 | 413.5 | 11.4 | 9.8 | 8.5 |
S1 | 8 932.7 | 451.5 | 451.5 | 8.9 | 8.9 |
S2 | 8 143.7 | 419.5 | 419.5 | 8.8 | 8.8 |
S3 | 8 923.9 | 493.4 | 12.5 | 8.7 | 7. 9 |
AVG | 8 866.4 | 424.3 | 295.7 | 9.1 | 8.8 |
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