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Artificial Bee Colony-Based Blind Watermarking Scheme for Color Images Alter Detection Using BRISK Features and DCT

  • Research Article-Computer Engineering and Computer Science
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Abstract

With the colossal development that the multimedia applications have currently reached, it is possible to manipulate the data contents easily. Thus, a receiver may get incorrect data compared to what the sender transmits. As a result, it is required to come up with an effective solution that checks the integrity of the received data, mainly images. In this context, we attempt through this paper to present a semi-fragile blind watermarking method using ABC, BRISK features and DCT. The method works on embedding the watermark data into specific area. As for the extraction stage, an authentication key is used to decide if the watermarked image was changed during transferring or not. Our findings show the efficiency of the proposed technique in terms of imperceptibility, robustness against some attacks, and tamper detection accuracy.

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References

  1. Amrit, P.; Singh, A.K.: Survey on watermarking methods in the artificial intelligence domain and beyond. Comput. Commun. 188, 52–65 (2022). https://doi.org/10.1016/j.comcom.2022.02.023

    Article  Google Scholar 

  2. Das, S.; Sunaniya, A.K.; Maity, R.; Maity, N.P.: Efficient FPGA implementation and verification of difference expansion based reversible watermarking with improved time and resource utilization. Microprocess. Microsyst. 83, 103732 (2021). https://doi.org/10.1016/j.micpro.2020.103732

    Article  Google Scholar 

  3. Sinhal, R.; Jain, D.K.; Ansari, I.A.: Machine learning based blind color image watermarking scheme for copyright protection. Pattern Recognit. Lett. 145, 171–177 (2021). https://doi.org/10.1016/j.patrec.2021.02.011

    Article  ADS  Google Scholar 

  4. Zhaoning, Y.; Yan, L.; Tiegang, G.: A lossless self-recovery watermarking scheme with JPEG-LS compression. J. Inf. Secur. Appl. 58, 102733 (2021). https://doi.org/10.1016/j.jisa.2020.102733

    Article  Google Scholar 

  5. Lefèvre, P.; Carré, P.; Fontaine, C.; Gaborit, P.; Huang, J.: Efficient image tampering localization using semi-fragile watermarking and error control codes. Signal Process. 190, 108342 (2022). https://doi.org/10.1016/j.sigpro.2021.108342

    Article  Google Scholar 

  6. Shivani, S.: Verifiable medical images for E-healthcare: a novel watermarking approach using robust bit-wise association of self-mutating offsprings of pixels. Microprocess. Microsyst. 90, 104483 (2022). https://doi.org/10.1016/j.micpro.2022.104483

    Article  Google Scholar 

  7. Horasan, F.: A novel image watermarking scheme using ULV decomposition. Opt. Int. J. Light Electron Opt. 259, 168958 (2022). https://doi.org/10.1016/j.ijleo.2022.168958

    Article  Google Scholar 

  8. Anand, A.; Singh, A.K.: An improved DWT-SVD domain watermarking for medical information security. Comput. Commun. 152, 72–80 (2020). https://doi.org/10.1016/j.comcom.2020.01.038

    Article  Google Scholar 

  9. Mellimi, S.; Rajput, V.; Ansari, I.A.; Ahn, C.W.: A fast and efficient image watermarking scheme based on deep neural network. Pattern Recognit. Lett. 151, 222–228 (2021). https://doi.org/10.1016/j.patrec.2021.08.015

    Article  ADS  Google Scholar 

  10. Li, Z.; Zhang, H.; Liu, X.; Wang, C.; Wang, X.: Blind and safety-enhanced dual watermarking algorithm with chaotic system encryption based on RHFM and DWT-DCT. Digit. Signal Process. 115, 103062 (2021). https://doi.org/10.1016/j.dsp.2021.103062

    Article  Google Scholar 

  11. Sinhal, R.; Sharma, S.; Ansari, I.A.; Bajaj, V.: Multipurpose medical image watermarking for effective security solutions. Multimed. Tools Appl. 81, 14045–14063 (2022). https://doi.org/10.1007/s11042-022-12082-0

    Article  PubMed  PubMed Central  Google Scholar 

  12. Qu, G.; Meng, X.; Yang, X.; Wu, H.; Wang, P.; He, W.; Chen, H.: Optical color watermarking based on single-pixel imaging and singular value decomposition in invariant wavelet domain. Opt. Lasers Eng. 137, 1–8 (2021). https://doi.org/10.1016/j.optlaseng.2020.106376

    Article  Google Scholar 

  13. Al-Otum, H.M.: Dual image watermarking using a multi-level thresholding and selective zone-quantization for copyright protection, authentication and recovery applications. Multimed. Tools Appl. (2022). https://doi.org/10.1007/s11042-022-11920-5

    Article  Google Scholar 

  14. Benrhouma, O.; Hermassi, H.; Abd El-Latif, A.A.; Belghith, S.: Chaotic watermark for blind forgery detection in images. Multimed. Tools Appl. (2015). https://doi.org/10.1007/s11042-015-2786-z

    Article  Google Scholar 

  15. Ullah, R.; Khan, A.; Malik, A.S.: Dual-purpose semi-fragile watermark: authentication and recovery of digital images. Comput. Electr. Eng. 39, 2019–2030 (2013). https://doi.org/10.1016/j.compeleceng.2013.04.024

    Article  Google Scholar 

  16. Singh, P.; Devi, K.J.; Thakkar, H.K.; Kotecha, K.: Region-based hybrid medical image watermarking scheme for robust and secured transmission in IoMT. IEEE ACESS (2022). https://doi.org/10.1109/ACCESS.2022.3143801

    Article  Google Scholar 

  17. Ouyang, J.; Huang, J.; Wen, X.; Shao, Z.: A semi-fragile watermarking tamper localization method based on QDFT and multi-view fusion. Multimed. Tools Appl. (2022). https://doi.org/10.1007/s11042-022-13938-1

    Article  Google Scholar 

  18. Leutenegger, S.; Chli, M.; Siegwart, R.Y.: BRISK: binary robust invariant scalable keypoints. Int. Conf. Comput. Vis. 2011, 2548–2555 (2011). https://doi.org/10.1109/ICCV.2011.6126542

    Article  Google Scholar 

  19. Karaboga, D.; Basturk, B.: Artificial Bee Colony (ABC) OptimizationAlgorithm for Solving Constrained Optimization Problems. In: Melin, P., Castillo, O., Aguilar, L.T., Kacprzyk, J., Pedrycz, W. (eds.) Foundations of Fuzzy Logic and Soft Computing, IFSA , Lecture Notes in Computer Science, vol. 4529 (2017). https://doi.org/10.1007/978-3-540-72950-1_77

  20. Sharma, S.S.; Chandrasekaran, V.: A robust hybrid digital watermarking technique against a powerful CNN-based adversarial attack. Multimed. Tools Appl. 79, 32769–32790 (2020). https://doi.org/10.1007/s11042-020-09555-5

    Article  Google Scholar 

  21. Soualmi, A.; Alti, A.; Laouamer, L.: A novel blind medical image watermarking scheme based on Schur triangulation and chaotic sequence. Concurr. Comput. Pract. Exp. (2021). https://doi.org/10.1002/cpe.6480

    Article  Google Scholar 

  22. http://tabby.vision.mcgill.ca/. Accessed 23 Apr 2022

  23. MATLAB (R2021a), Natick, Massachusetts: The MathWorks Inc (2021)

  24. Wan, W.; Wang, J.; Zhang, Y.; Li, J.; Yu, H.; Sun, J.: A comprehensive survey on robust image watermarking. Neurocomputing 488, 226–247 (2022). https://doi.org/10.1016/j.neucom.2022.02.083

    Article  Google Scholar 

  25. Soualmi, A.; Alti, A.; Laouamer, L.: Multiple blind watermarking framework for security and integrity of medical images in E-health applications. Int. J. Comput. Vis. Image Process. 11(1), 1–16 (2021). https://doi.org/10.4018/IJCVIP.2021010101

    Article  Google Scholar 

  26. Prasad, S.; Pal, A.K.; Paul, S.: A block-level image tamper detection scheme using modulus function based fragile watermarking. Wirel. Pers. Commun. (2022). https://doi.org/10.1007/s11277-022-09675-1

    Article  PubMed  PubMed Central  Google Scholar 

  27. Sivananthamaitrey, P.; Kumar, P.R.: High embedding capacity dual digital watermarking using stationary wavelet transform. Mater. Today Proc. (2021). https://doi.org/10.1016/j.matpr.2021.01.711

    Article  Google Scholar 

  28. Petitcolas, F.: Watermarking stirmark (2012). http://www.petitcolas.net/fabien/watermarking /stirmark/

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Correspondence to Abdallah Soualmi.

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Soualmi, A., Benhocine, A. & Midoun, I. Artificial Bee Colony-Based Blind Watermarking Scheme for Color Images Alter Detection Using BRISK Features and DCT. Arab J Sci Eng 49, 3253–3266 (2024). https://doi.org/10.1007/s13369-023-07958-8

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  • DOI: https://doi.org/10.1007/s13369-023-07958-8

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