Image Tampering Detection and Localization
A list of papers, codes and other interesting collections pertaining to image tampering detection and localization.
Classical Filter Based Methods
- Wang, Wei, Jing Dong, and Tieniu Tan. "Image tampering detection based on stationary distribution of Markov chain." In ICIP, 2010. pdf
- Hsu, Yu-Feng, and Shih-Fu Chang. "Statistical fusion of multiple cues for image tampering detection." 42nd Asilomar Conference on Signals, Systems and Computers, 2008. pdf
- Tong, Xiaojun, et al. "A novel chaos-based fragile watermarking for image tampering detection and self-recovery." Signal Processing: Image Communication 28.3 (2013). pdf
- Goh, Jonathan, and Vrizlynn LL Thing. "A hybrid evolutionary algorithm for feature and ensemble selection in image tampering detection." International Journal of Electronic Security and Digital Forensics 7.1 (2015). pdf
- Dong, Jing, Wei Wang, and Tieniu Tan. "Casia image tampering detection evaluation database." IEEE China Summit & International Conference on Signal and Information Processing, 2013. pdf
- Fan, Jiayuan, Tao Chen, and Jiuwen Cao. "Image tampering detection using noise histogram features." IEEE International Conference on Digital Signal Processing, 2015. pdf
- Gaborini, Lorenzo, et al. "Multi-clue image tampering localization." IEEE International Workshop on Information Forensics and Security, 2014. pdf
- Birajdar, Gajanan K., and Vijay H. Mankar. "Digital image forgery detection using passive techniques: A survey." Digital Investigation 10.3, 2013. pdf
- Muhammad, Ghulam, et al. "Image forgery detection using steerable pyramid transform and local binary pattern." Machine Vision and Applications 25.4, 2014. pdf
- Pun, Chi-Man, Xiao-Chen Yuan, and Xiu-Li Bi. "Image forgery detection using adaptive oversegmentation and feature point matching." IEEE Transactions on Information Forensics and Security, 2015. pdf
- Cozzolino, Davide, Diego Gragnaniello, and Luisa Verdoliva. "Image forgery detection through residual-based local descriptors and block-matching." IEEE International Conference on Image Processing (ICIP), 2014. pdf
- Jaberi, Maryam, et al. "Accurate and robust localization of duplicated region in copy–move image forgery." Machine vision and applications, 2014. pdf
- Qazi, Tanzeela, et al. "Survey on blind image forgery detection." IET Image Processing, 2013. pdf
- Lynch, Gavin, Frank Y. Shih, and Hong-Yuan Mark Liao. "An efficient expanding block algorithm for image copy-move forgery detection." Information Sciences, 2013. pdf
- Zhao, Jie, and Jichang Guo. "Passive forensics for copy-move image forgery using a method based on DCT and SVD." Forensic science international, 2013. pdf
- Kashyap, Abhishek, et al. "An Evaluation of Digital Image Forgery Detection Approaches." arXiv preprint arXiv:1703.09968, 2017. pdf
- Li, Haodong, et al. "Image Forgery Localization via Integrating Tampering Possibility Maps." IEEE Transactions on Information Forensics and Security, 2017. pdf
- Hashmi, Mohammad Farukh, Vijay Anand, and Avinash G. Keskar. "A copy-move image forgery detection based on speeded up robust feature transform and Wavelet Transforms." International Conference on Computer and Communication Technology (ICCCT), 2014. pdf
- Farid, Hany. "Image forgery detection." IEEE Signal processing magazine, 2009. pdf
- Bianchi, Tiziano, and Alessandro Piva. "Image forgery localization via block-grained analysis of JPEG artifacts." IEEE Transactions on Information Forensics and Security, 2012. pdf
- Muhammad, Ghulam, Muhammad Hussain, and George Bebis. "Passive copy move image forgery detection using undecimated dyadic wavelet transform." Digital Investigation, 2012. pdf
- Chen, Can, Scott McCloskey, and Jingyi Yu. "Image Splicing Detection via Camera Response Function Analysis." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2017. pdf
Deep Learning based Methods
- Chen, Jiansheng, et al. "Median filtering forensics based on convolutional neural networks." IEEE Signal Processing Letters, 2015. pdf
- Bayar, Belhassen, and Matthew C. Stamm. "A deep learning approach to universal image manipulation detection using a new convolutional layer." Proceedings of the 4th ACM Workshop on Information Hiding and Multimedia Security, 2016. pdf
- Liu, Yaqi, et al. "Image Forgery Localization Based on Multi-Scale Convolutional Neural Networks." arXiv preprint arXiv:1706.07842 (2017). pdf
- Rao, Yuan, and Jiangqun Ni. "A deep learning approach to detection of splicing and copy-move forgeries in images." IEEE International Workshop on Information Forensics and Security (WIFS), 2016. pdf
- Bayar, Belhassen, and Matthew C. Stamm. "On the robustness of constrained convolutional neural networks to jpeg post-compression for image resampling detection." IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017. pdf
- Zhou, Jianghong, Jiangqun Ni, and Yuan Rao. "Block-Based Convolutional Neural Network for Image Forgery Detection." International Workshop on Digital Watermarking. Springer, 2017.
- Choi, Hak-Yeol, et al. "Detecting composite image manipulation based on deep neural networks." 2017 International Conference on Systems, Signals and Image Processing (IWSSIP), 2017. pdf
- Bondi, Luca, et al. "Tampering Detection and Localization through Clustering of Camera-Based CNN Features." 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2017. pdf
- Bappy, Jawadul H., et al. "Exploiting Spatial Structure for Localizing Manipulated Image Regions." Proceedings of the IEEE International Conference on Computer Vision (ICCV). 2017. pdf
- Bunk, Jason, et al. "Detection and Localization of Image Forgeries using Resampling Features and Deep Learning." IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2017. pdf
- Wang, Qing, and Rong Zhang. "Double JPEG compression forensics based on a convolutional neural network." EURASIP Journal on Information Security, 2016. pdf
- Salloum, Ronald, Yuzhuo Ren, and C-C. Jay Kuo. "Image Splicing Localization Using A Multi-Task Fully Convolutional Network (MFCN)." arXiv preprint arXiv:1709.02016 (2017). pdf
- Rota, Paolo, et al. "Bad teacher or unruly student: Can deep learning say something in Image Forensics analysis?." 23rd International Conference on Pattern Recognition (ICPR), 2016. pdf
- Böhme, Rainer, and Matthias Kirchner. "Counter-forensics: Attacking image forensics." Digital Image Forensics. Springer New York, 2013. pdf
- Raghavendra, R., et al. "Transferable Deep-CNN features for detecting digital and print-scanned morphed face images." 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2017. pdf
- Bondi, Luca, et al. "Tampering Detection and Localization through Clustering of Camera-Based CNN Features." IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2017. pdf