融合彩色信息与SIFT特征的帧内复制粘贴篡改检测
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摘要
近年来在同源复制粘贴篡改检测中,SIFT特征得到了广泛的应用.但由于该特征在提取过程中摒弃了颜色信息,会造成一部分特征点的误匹配和漏匹配.为此,提出一种基于彩色信息与SIFT融合的CSIFT特征的检测方法,在提取特征点时加入颜色不变量信息,提高了匹配的准确性和效率.算法首先利用结构相似度将视频帧序列分段,提取每段序列的关键帧;然后提取关键帧的CSIFT特征;最终定位复制粘贴区域,并利用目标跟踪算法计算篡改区域在后续帧上的位置.通过实验验证了算法的鲁棒性,与基于SIFT等特征的算法相比,时间效率和准确性更高.
SIFT feature has been widely used in the homologous copy-paste forgery detection.Due to the rejection of color information,it results in some mismatching of key points,so we propose another method based on Colored Scale Invariant Feature Transform(CSIFT),a feature combining variable color information with Scale Invariant Feature Transform(SIFT)when extracting feature points decreasing the possibility of false matching and greatly reducing the time of feature point extraction and matching.In this study,we firstly segment video by Structural Similarity Index Measurement(SSIM)and extract the first frame of every part as the key frame.Then,we extract CSIFT feature points of the key frame and match feature points.After that,we locate copy-paste areas.The final step is a target tracking algorithm used to calculate the copy-paste areas in the following frame sequence.The robustness and efficiency of the algorithm is verified by experiments.Compared with algorithms based on SIFT,the proposed method has higher time efficiency and accuracy.
SIFT feature has been widely used in the homologous copy-paste forgery detection.Due to the rejection of color information,it results in some mismatching of key points,so we propose another method based on Colored Scale Invariant Feature Transform(CSIFT),a feature combining variable color information with Scale Invariant Feature Transform(SIFT)when extracting feature points decreasing the possibility of false matching and greatly reducing the time of feature point extraction and matching.In this study,we firstly segment video by Structural Similarity Index Measurement(SSIM)and extract the first frame of every part as the key frame.Then,we extract CSIFT feature points of the key frame and match feature points.After that,we locate copy-paste areas.The final step is a target tracking algorithm used to calculate the copy-paste areas in the following frame sequence.The robustness and efficiency of the algorithm is verified by experiments.Compared with algorithms based on SIFT,the proposed method has higher time efficiency and accuracy.
引文
1卢贺楠,黄添强,林晶.基于动态阈值的帧复制粘贴篡改检测.计算机系统应用,2016,25(12):108-116.[doi:10.15888/j.cnki.csa.005499]
2 Su LC,Li CH,Lai YC,et al.A fast forgery detection algorithm based on exponential-Fourier moments for video region duplication.IEEE Transactions on Multimedia,2017.[doi:10.1109/TMM.2017.2760098]
3 Subramanyam AV,Emmanuel S.Video forgery detection using HOG features and compression properties.IEEE 14th International Workshop on Multimedia Signal Processing.Banff,Canada.2012.89-94.
4 Wang WH,Farid H.Exposing digital forgeries in video by detecting double quantization.Proceedings of the 11th ACM Workshop on Multimedia and Security.Princeton,NJ,USA.2009.39-48.
5 Chen W,Shi YQ.Detection of double MPEG compression based on first digit statistics.In:Kim HJ,Katzenbeisser S,Ho ATS,eds.Digital Watermarking.Berlin,Heidelberg.Springer.2009.
6 Zhang J,Su YT,Zhang MY.Exposing digital video forgery by ghost shadow artifact.Proceedings of the First ACM Workshop on Multimedia in Forensics.Beijing,China.2009.49-54.
7 Pandey RC,Singh SK,Shukla KK.Passive forensics in image and video using noise features:A review.Digital Investigation,2016,(19):1-28.
8杜振龙,焦丽鑫,李晓丽,等.帧内复制粘贴视频伪造的盲检测.中国图象图形学报,2014,19(6):825-834.
9赵洁,郭继昌,张艳,等.JPEG图像双重压缩偏移量估计的篡改区域自动检测定位.中国图象图形学报,2015,20(10):1304-1312.[doi:10.11834/jig.20151003]
10 Warbhe AD,Dharaskar RV,Thakare VM.A survey on keypoint based copy-paste forgery detection techniques.Procedia Computer Science,2016,(78):61-67.[doi:10.1016/j.procs.2016.02.011]
11林晶,黄添强,林玲鹏,等.采用局部强度顺序模式的图像复制一粘贴篡改检测算法.通信学报,2016,37(Z1):132-139.[doi:10.11959/j.issn.1000-436x.2016259]
12 Abdel-Hakim AE,Farag AA.CSIFT:A sift descriptor with color invariant characteristics.2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.New York,NY,USA.2006.1978-1983.
13朱叶,申铉京,陈海鹏.基于彩色LBP的隐蔽性复制-粘贴篡改盲鉴别算法.自动化学报,2017,43(3):390-397.
14 Geusebroek JM,Van den Boomgaard R,Smeulders AWM,et al.Color invariance.IEEE Transactions on Pattern Analysis and Machine Intelligence,2001,23(12):1338-1350.[doi:10.1109/34.977559]
15 Kubelka P.New contributions to the optics of intensely light-scattering materials.Part II:Nonhomogeneous layers.Journal of the Optical Society of America,1954,44(4):330-335.[doi:10.1364/JOSA.44.000330]
16 Wyszecki G,Stiles VS,Kelly KL.Color science:Concepts and methods,quantitative data and formulas.Physics Today,1968,21(6):83.[doi:10.1063/1.3035025]
17 Lowe DG.Distinctive image features from scale-invariant keypoints.International Journal of Computer Vision,2004:91-110.
18 Wang Z,Bovik AC,Sheikh HR,et al.Image quality assessment:From error visibility to structural similarity.IEEE Transactions on Image Processing,2004,13(4):600-612.[doi:10.1109/TIP.2003.819861]
19 Wang WH,Farid H.Exposing digital forgeries in video by detecting duplication.Proceedings of the 9th ACM Workshop on Multimedia&Security.Dallas,TX,USA.2007.35-42.
2 Su LC,Li CH,Lai YC,et al.A fast forgery detection algorithm based on exponential-Fourier moments for video region duplication.IEEE Transactions on Multimedia,2017.[doi:10.1109/TMM.2017.2760098]
3 Subramanyam AV,Emmanuel S.Video forgery detection using HOG features and compression properties.IEEE 14th International Workshop on Multimedia Signal Processing.Banff,Canada.2012.89-94.
4 Wang WH,Farid H.Exposing digital forgeries in video by detecting double quantization.Proceedings of the 11th ACM Workshop on Multimedia and Security.Princeton,NJ,USA.2009.39-48.
5 Chen W,Shi YQ.Detection of double MPEG compression based on first digit statistics.In:Kim HJ,Katzenbeisser S,Ho ATS,eds.Digital Watermarking.Berlin,Heidelberg.Springer.2009.
6 Zhang J,Su YT,Zhang MY.Exposing digital video forgery by ghost shadow artifact.Proceedings of the First ACM Workshop on Multimedia in Forensics.Beijing,China.2009.49-54.
7 Pandey RC,Singh SK,Shukla KK.Passive forensics in image and video using noise features:A review.Digital Investigation,2016,(19):1-28.
8杜振龙,焦丽鑫,李晓丽,等.帧内复制粘贴视频伪造的盲检测.中国图象图形学报,2014,19(6):825-834.
9赵洁,郭继昌,张艳,等.JPEG图像双重压缩偏移量估计的篡改区域自动检测定位.中国图象图形学报,2015,20(10):1304-1312.[doi:10.11834/jig.20151003]
10 Warbhe AD,Dharaskar RV,Thakare VM.A survey on keypoint based copy-paste forgery detection techniques.Procedia Computer Science,2016,(78):61-67.[doi:10.1016/j.procs.2016.02.011]
11林晶,黄添强,林玲鹏,等.采用局部强度顺序模式的图像复制一粘贴篡改检测算法.通信学报,2016,37(Z1):132-139.[doi:10.11959/j.issn.1000-436x.2016259]
12 Abdel-Hakim AE,Farag AA.CSIFT:A sift descriptor with color invariant characteristics.2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.New York,NY,USA.2006.1978-1983.
13朱叶,申铉京,陈海鹏.基于彩色LBP的隐蔽性复制-粘贴篡改盲鉴别算法.自动化学报,2017,43(3):390-397.
14 Geusebroek JM,Van den Boomgaard R,Smeulders AWM,et al.Color invariance.IEEE Transactions on Pattern Analysis and Machine Intelligence,2001,23(12):1338-1350.[doi:10.1109/34.977559]
15 Kubelka P.New contributions to the optics of intensely light-scattering materials.Part II:Nonhomogeneous layers.Journal of the Optical Society of America,1954,44(4):330-335.[doi:10.1364/JOSA.44.000330]
16 Wyszecki G,Stiles VS,Kelly KL.Color science:Concepts and methods,quantitative data and formulas.Physics Today,1968,21(6):83.[doi:10.1063/1.3035025]
17 Lowe DG.Distinctive image features from scale-invariant keypoints.International Journal of Computer Vision,2004:91-110.
18 Wang Z,Bovik AC,Sheikh HR,et al.Image quality assessment:From error visibility to structural similarity.IEEE Transactions on Image Processing,2004,13(4):600-612.[doi:10.1109/TIP.2003.819861]
19 Wang WH,Farid H.Exposing digital forgeries in video by detecting duplication.Proceedings of the 9th ACM Workshop on Multimedia&Security.Dallas,TX,USA.2007.35-42.