Document Type : Research Article


1 Department of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran

2 Faculty of Technology and Engineering, Shahrekord University, Shahrekord, Iran


Fragile watermarking is the task of embedding a watermark in a media (an image in this paper) such that even small changes, called tamper, can be detected or even recovered to prevent unauthorized alteration. A well-known category of spatial fragile watermarking methods is based on embedding the watermark in the least significant bits of the image to preserve the quality. In addition, Hamming code is a coding algorithm in communication that transmits the data-bits by augmenting some check-bits in order to exactly detect and recover single-bit modifications. This property is previously used to detect and perfectly recover the images modified by small tampers less than a quarter of the image in diameter. To achieve this goal, the Hamming code is applied on a distributed pixel, bits of which are gathered from sufficient far pixels in the image. It guarantees that such tampers can toggle at most one bit of each distributed Hamming code that is recoverable. It was the only guaranteed perfect reconstruction method of small tampers, based on our knowledge. In this paper, the method has been extended to support distortion in two bits of a Hamming code by use of common structures of distributed codes. It leads to guarantee recovery of tampers less than half of the image in width and height. According to the experimental results, the proposed method achieved better performance, in terms of recovering the tampered areas, in comparison to state-of-the-art.


[1] Satendra Pal Singh and Gaurav Bhatnagar. A new robust watermarking system in integer dct domain. Journal of Visual Communication and Image Representation, 53:86–101, 2018.
[2] Xiaobing Kang, Yajun Chen, Fan Zhao, and Guangfeng Lin. Multi-dimensional particle swarm optimization for robust blind image watermarking using intertwining logistic map and hybrid domain. Soft Computing, 24(14):10561–10584, 2020.
[3] Imran Sikder, Pranab Kumar Dhar, and Tetsuya Shimamura. A semi-fragile watermarking method using slant transform and lu decomposition for image authentication. In 2017 International Conference on Electrical, Computer and Communication Engineering (ECCE), pages 881–885. IEEE, 2017.
[4] Richard W Hamming. Error detecting and error correcting codes. The Bell system technical journal, 29(2):147–160, 1950.
[5] Phen Lan Lin, Chung-Kai Hsieh, and Po-Whei Huang. A hierarchical digital watermarking method for image tamper detection and recovery. Pattern recognition, 38(12):2519–2529, 2005.
[6] Tien-You Lee and Shinfeng D Lin. Dual watermark for image tamper detection and recovery. Pattern recognition, 41(11):3497–3506, 2008.
[7] Dipabali Sarkar, Sarbani Palit, Sukalyan Som, and KN Dey. Large scale image tamper detection and restoration. Multimedia Tools and Applications, 79(25):17761–17791, 2020.
[8] Chi-Shiang Chan. An image authentication method by applying hamming code on rearranged bits. Pattern Recognition Letters, 32(14):1679–1690, 2011.
[9] Chi-Shiang Chan and Chin-Chen Chang. An efficient image authentication method based on hamming code. Pattern Recognition, 40(2):681–690, 2007.
[10] Surya Bhagavan Chaluvadi and Munaga VNK Prasad. Efficient image tamper detection and recovery technique using dual watermark. In 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), pages 993–998. IEEE, 2009.
[11] Faranak Tohidi and Manoranjan Paul. A new image watermarking scheme for efficient tamper detection, localization and recovery. In 2019 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), pages 19–24. IEEE, 2019.
[12] Irshad Ahmad Ansari, Millie Pant, and Chang Wook Ahn. Svd based fragile watermarking scheme for tamper localization and selfrecovery. International Journal of Machine Learning and Cybernetics, 7(6):1225–1239, 2016.
[13] Durgesh Singh and Sanjay K Singh. Dct based efficient fragile watermarking scheme for image authentication and restoration. Multimedia Tools and Applications, 76(1):953–977, 2017.
[14] Behrouz Bolourian Haghighi, Amir Hossein Taherinia, and Amir Hossein Mohajerzadeh. Trlg: Fragile blind quad watermarking for image tamper detection and recovery by providing compact digests with optimized quality using lwt and ga.Information Sciences, 486:204–230, 2019.
[15] Navid Daneshmandpour, Habibollah Danyali, and Mohammad Sadegh Helfroush. Image tamper detection and multiscale self-recovery using reference embedding with multi-rate data protection. China Communications, 16(11):154–166, 2019.
[16] Faeze Rasouli and Mohammad Taheri. A new fragile watermarking based on distributed hamming code. In 2021 26th International Computer Conference, Computer Society of Iran (CSICC), pages 1–5. IEEE, 2021.
[17] Zhou Wang, Eero P Simoncelli, and Alan C Bovik. Multiscale structural similarity for image quality assessment. In The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003, volume 2, pages 1398–1402. Ieee, 2003.
[18] Vishal Rajput and Irshad Ahmad Ansari. Image tamper detection and self-recovery using multiple median watermarking. Multimedia Tools and Applications, 79(47):35519–35535, 2020.
[19] Assem Abdelhakim, Hassan I Saleh, and Mai Abdelhakim. Fragile watermarking for image tamper detection and localization with effective recovery capability using k-means clustering. Multimedia Tools and Applications, 78(22):32523–32563, 2019.
[20] Omer Hemida and Hongjie He. A self-recovery watermarking scheme based on block truncation coding and quantum chaos map. Multimedia Tools and Applications, 79(25):18695–18725, 2020.
[21] Ziyun Xia, Wenyin Zhang, Huichuan Duan, Jiuru Wang, and Xiuyuan Wei. Fragile watermarking scheme in spatial domain based on prime number distribution theory. Multimedia Tools and Applications, 81(5):6477–6496, 2022.
[22] Afrig Aminuddin and Ferda Ernawan. Ausr1: Authentication and self-recovery using a new image inpainting technique with lsb shifting in fragile image watermarking. Journal of King Saud University-Computer and Information Sciences, 2022.
[23] Li Huang, Da Kuang, Cheng-long Li, Yu-jian Zhuang, Shao-hua Duan, and Xiao-yi Zhou. A self embedding secure fragile watermarking scheme with high quality recovery. Journal of Visual Communication and Image Representation, 83:103437, 2022.
[24] Payal Garg and Ajit Kumar Jain. Digital watermarking techniques and their analysis. In Smart Systems: Innovations in Computing, pages 41–54. Springer, 2022.
[25] Saeed Sarreshtedari, Aliazam Abbasfar, and Mohammad Ali Akhaee. A joint source–channel coding approach to digital image self-recovery. Signal, Image and Video Processing, 11(7):1371–1378, 2017.