Abstract
This paper proposes an approach to protect image content against malicious tampering based on watermarking technology. The watermark is composed of two kinds of check bits which are used for tampered region localization, and one recovery bit which is used for image recovery and is embedded into the three-Least Significant Bit planes of the original image. The first check bit is generated by applying the proposed Parity Check Bit Labeled method to each pixel, and the other is generated by employing hashing algorithm to each block after image decomposition. The superposition result detected from the two check bits contributes to lowering the probability of false-negative errors. Moreover, we propose a post-processing method Adaptive Structural Element Calculation which improves the accuracy of tamper detection result further. Experimental results show that our algorithm has good performance in keeping high quality of recovered image, and meanwhile improving the accuracy of tamper detection result.















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References
Abdulla AA (2015) "Exploiting similarities between secret and cover images for improved embedding efficiency and security in digital steganography," University of Buckingham
Agarwal R, Verma OP (2019) An efficient copy move forgery detection using deep learning feature extraction and matching algorithm. Multimedia Tools Applications:1–22
AlShehri L, Hussain M, Aboalsamh H, Wadood A (2020) Fragile watermarking for image authentication using BRINT and ELM. Multimedia Tools and Applications 79:29199–29223
Ansari IA, Pant M, Ahn CW (2016) SVD based fragile watermarking scheme for tamper localization and self-recovery. International Journal of Machine Learning and Cybernetics 7:1225–1239
Bas P, Furon T (2007) "BOWS-2, http://bows2.eclille.fr/index.php?mode=VIEW&tmpl=index1.," .
Cao F, An B, Wang J, Ye D, Wang H (2017) Hierarchical recovery for tampered images based on watermark self-embedding. Displays 46:52–60
Chang Y-F, Tai W-L (2013) A block-based watermarking scheme for image tamper detection and self-recovery. Opto-Electronics Review 21(2):182–190
Chen W-C, Wang M-S (2009) A fuzzy c-means clustering-based fragile watermarking scheme for image authentication. Expert Syst Appl 36(2):1300–1307
Dhole VS, Patil NN (2015) "Self embedding fragile watermarking for image tampering detection and image recovery using self recovery blocks," in 2015 International Conference on Computing Communication Control and Automation, pp. 752–757: IEEE
Di Martino F, Sessa S (2012) Fragile watermarking tamper detection with images compressed by fuzzy transform. Information Sciences 195:62–90
Di Martino F, Sessa S (2019) Fragile watermarking tamper detection via bilinear fuzzy relation equations. Journal of Ambient Intelligence and Humanized Computing 10:2041–2061
Douglas M, Bailey K, Leeney M, Curran K (2018) An overview of steganography techniques applied to the protection of biometric data. Multimedia Tools and Applications 77:17333–17373
Elaskily MA, Elnemr HA, Dessouky MM, Faragallah OS (2019) Two stages object recognition based copy-move forgery detection algorithm. Multimedia Tools and Applications 78:15353–15373
Eswaraiah R, Sreenivasa Reddy E (2015) Robust medical image watermarking technique for accurate detection of tampers inside region of interest and recovering original region of interest. IET Image Processing 9:615–625
Falkenstern KR, Reed AM, Holub V, Rodriguez TF (2019) "digital watermarking and data hiding with narrow-band absorption materials," ed: Google patents
Gao Y, Wang Ji, Shi Y-Q (2019) Dynamic multi-watermarking and detecting in DWT domain. Journal of Real-Time Image Processing 16:565–576
Gong D, Chen Y, Lu H, Li Z, Han Y (2018) Self-embedding Image Watermarking based on Combined Decision Using Pre-offset and Post-offset Blocks. Computers, Materials & Continua 57:243–260
Kaur N, Jindal N, Singh K (2020) A passive approach for the detection of splicing forgery in digital images. Multimedia Tools and Applications 79:32037–32063
Liu K-C (2012) Colour image watermarking for tamper proofing and pattern-based recovery. (in En), IET Image Processing 6(5):445–454
Mishra S, Markam K, (2018) "Analysis of active and passive mechanism for image forgery detection
Moghaddasi Z, Jalab HA, Noor RM (2019) Image splicing forgery detection based on low-dimensional singular value decomposition of discrete cosine transform coefficients. Neural Computing and Applications 31:7867–7877
Molina J, Ponomaryov V, Reyes R, Sadovnychiy S, Cruz C (2020) Watermarking framework for authentication and self-recovery of tampered colour images. IEEE Lat Am Trans 18(03):631–638
Nazari M, Sharif A, Mollaeefar M (2017) An improved method for digital image fragile watermarking based on chaotic maps. Multimedia Tools and Applications 76:16107–16123
Pal P, Jana B, Bhaumik J (2019) Robust watermarking scheme for tamper detection and authentication exploiting CA. (in En), IET Image Processing 13(12):2116–2129
Qin C, Ji P, Zhang X, Dong J, Wang J (2017) Fragile image watermarking with pixel-wise recovery based on overlapping embedding strategy. Signal Processing 138:280–293
Qin C, Qian Z, Feng G, Zhang X (2019) Special issue on real-time image watermarking and forensics in cloud computing. Journal of Real-Time Image Processing 16:559–563
Rajput V, Ansari IA (2020) Image tamper detection and self-recovery using multiple median watermarking. Multimedia Tools and Applications 79:35519–35535
Said A, Pearlman WA (1996) A new, fast, and efficient image codec based on set partitioning in hierarchical trees. IEEE Transactions on circuits and systems for video technology 6(3):243–250
Sarkar D, Palit S, Som S, Dey KN (2020) Large scale image tamper detection and restoration. Multimedia Tools and Applications 79:17761–17791
Sarreshtedari S, Akhaee MA (2015) A source-channel coding approach to digital image protection and self-recovery. IEEE Trans Image Process 24(7):2266–2277
Sedighi V, Cogranne R, Fridrich J (2015) Content-adaptive steganography by minimizing statistical detectability. IEEE Transactions on Information Forensics and Security 11(2):221–234
Singh D, Singh SK (2017) DCT based efficient fragile watermarking scheme for image authentication and restoration. Multimed Tools Appl 76(1):953–977
Steve W (1995) Information authentication for a slippery new age. Dr Dobbs Journal:18–26
Su Z, Yao L, Mei J, Zhou L, Li W (2020) "Learning to hash for personalized image authentication," IEEE Transactions on Circuits and Systems for Video Technology
Tagliasacchi M, Valenzise G, Tubaro S (2009) Hash-based identification of sparse image tampering. IEEE Trans Image Process 18(11):2491–2504
Yang Q, Yu D, Zhang Z, Yao Y, Chen L, (2020) "Spatiotemporal trident networks: detection and localization of object removal tampering in video passive forensics," IEEE Transactions on Circuits and Systems for Video Technology, 1
Yao H, Wei H, Qin C, Tang Z (2020) A real-time reversible image authentication method using uniform embedding strategy. Journal of Real-Time Image Processing 17:41–54
Acknowledgments
This work was supported by the National Natural Science Foundation of China (Grant No. 61902448) and the Research Fund of Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology (Grant No. 2020B1212030010).
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Liu, T., Yuan, X. A dual-tamper-detection method for digital image authentication and content self-recovery. Multimed Tools Appl 80, 29805–29826 (2021). https://doi.org/10.1007/s11042-021-11179-2
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DOI: https://doi.org/10.1007/s11042-021-11179-2