Neutrosophic Domain for Image Zero Watermarking

Neutrosophic Domain for Image Zero Watermarking

Authors

  • Hussein Kadhim Abdali Department of Mathematics and Computer Applications, College of Applied Sciences, University of Technology, Al-sinaa Street, Baghdad 10001, Iraq
  • Areej M. Abduldaima Department of Mathematics and Computer Applications, College of Applied Sciences, University of Technology, Al-sinaa Street, Baghdad 10001, Iraq
  • Matheel E. Abdulmunim bMultimedia and Digital Media Department, College of Computer Sciences, University of Technology, Al-sinaa Street, Baghdad 10001, Iraq

DOI:

https://doi.org/10.29304/jqcsm.2026.18.22948

Keywords:

Membership Functions, Neutrosophic Domain, Image Zero Watermarking, Zero Watermark Construction, Watermark Recovery

Abstract

In our time, the use of various technological application systems has become an accepted and indispensable necessity. Naturally, the use of images in these applications is a priority due to the significant impact of image circulation, whether for medical, industrial, economic, or, of course, social and personal purposes. Therefore, the ease with which this vast amount of data is shared has led to significant challenges in terms of security, intellectual property rights protection, and other areas. Consequently, watermarking technologies, especially zero-based watermarking, have become an ideal solution for preserving images, provided that ownership is securely verified without any alteration to the original images. This research aims to propose a developed zero-watermarking model using: 1- A neutrosophic domain, which is used to extract important image features and use them to generate new features. 2- Calculating the average of each block to create a new, more stable feature matrix. Initially, the image is converted to a neutrosophic domain, and the component T is selected and divided into non-overlapping blocks, each of size 4x4. Accordingly, a feature matrix is ​​created whose elements are the average values ​​of each block and converted to binary form, where the watermark is merged with it through XOR to build the zero watermark.

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References

M. Barni, F. Bartolini, and A. Piva, “Improved Wavelet-Based Watermarking Through Pixel-Wise Masking,” IEEE Transactions on Image Processing, vol. 10, no. 5, pp. 783–791, 2001.

X. Kang, J. Huang, Y. Q. Shi, and Y. Lin, “A DWT-DFT Composite Watermarking Scheme Robust to Both Affine Transform and JPEG Compression,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 13, no. 8, pp. 776–786, 2003.

C.-C. Chang, P. Tsai, and C.-C. Lin, “SVD-Based Digital Image Watermarking Scheme,” Pattern Recognition Letters, vol. 26, no. 10, pp. 1577–1586, Elsevier, 2005.

A.M. Abduldaim, N.M.G. Al-Saidi, A.K. Faraj, and S.A. Alameer Kadhim, “Enhancing Image Security through PCA-IWT-Based Nil Steganography under Distortion Scenarios,” Boletim da Sociedade Paranaense de Matemática, vol. 43, no. 3, (2025), pp. 1–18.

A.F. Mutlk, A.M. Abdmldaim, and M.E. Abdulmunim, “Employing Algebraic Eigenvalue Decomposition in Zero Watermarking Technology,” International Journal of Mathematics and Computer Science, vol. 20, no. 1, (2025), pp. 333–343.

F. Smarandache, Neutrosophy: Neutrosophic Probability, Set, and Logic: Analytic Synthesis & Synthetic Analysis. Rehoboth: American Research Press, (1998).

Y. Guo and H.D. Cheng, “New neutrosophic approach to image segmentation,” Pattern Recognition, vol. 42, no. 5, (2009), pp. 587-595.

H.D. Cheng, Y. Guo, and Y. Zhang, “A novel image segmentation approach based on neutrosophic set and improved fuzzy C-means algorithm,” New Mathematics and Natural Computation, vol. 7, no. 1, (2011), pp. 155-171.

J. Wen, S. Xuan, Y. Li, Q. Peng, and Q. Gao, “Image segmentation algorithm based on neutrosophic fuzzy clustering with non-local information,” IET Image Processing, vol. 14, no. 3, (2020), pp. 576-584.

B. Yu, Z. Niu, and L. Wang, “Mean shift-based clustering of neutrosophic domain for unsupervised constructions detection,” Optik, vol. 124, no. 21, (2013), pp. 4697-4706.

Y. Guo and A. Sengür, “A novel image edge detection algorithm based on neutrosophic set,” Computers & Electrical Engineering, vol. 40, no. 8, (2014), pp. 3-25.

A.A. Salama, M. Eisa, and A.E. Fawzy, “A neutrosophic image retrieval classifier,” International Journal of Computer Applications, vol. 170, no. 9, (2017), pp. 1-6.

G. Yang, X. Lu, Y. Lu, J. Tang, and X. Xiong, “Robust zero-watermarking method for multiple medical images using wavelet fusion and DTCWT-QR,” Journal of Information Security and Applications, vol. 90, (2025), Art. no. 103945.

I.W. Elhamzi, “Enhancing medical image security with FPGA-accelerated LED cryptography and LSB watermarking,” Traitement du Signal, vol. 41, no. 1, (2024), pp. 85-97.

R. Purnima, A. Rakesh, and N. Gautam, “Motion-frames based video watermarking scheme for copyright protection using guided filtering in wavelet domain,” Traitement du Signal, vol. 40, no. 1, (2023), pp. 187-197.

R. Riyajuddin and A.P. Reddy, “Various image processing attacks for image watermarking in the wavelet domain using singular value decomposition and discrete cosine transform,” Review of Computer Engineering Studies, vol. 8, no. 2, (2021), pp. 51-59.

Taha Basheer Taha, Huda E. Khalid, Neutrosophic Similarity Measure for Assessing Digital Watermarked Images, Neutrosophic Sets and Systems, Vol. 61, 2023, 53-68.

Atta R, Ghanbari M. A high payload steganography mechanism based on wavelet packet transformation and neutrosophic set. J Vis Commun Image Represent. 2018;53:42–54.

Ming Zhang, Ling Zhang, H.D. Cheng, A neutrosophic approach to image segmentation based on watershed method, Signal Processing 90 (2010) 1510–1517.

Amanna Ghanbari Talouki, Abbas Koochari, Image completion based on segmentation using neutrosophic sets, Expert Systems with Applications, Volume 238, Part A, 2024.

Z. Pan, C. Wu, C. Yang, and B. Zhao, “Double-matrix decomposition image steganography scheme based on wavelet transform with multi-region coverage,” Entropy, vol. 24, no. 2, (2022), Art. no. 246.

Q. Su, Y. Sun, Y. Xia, and Z. Wang, “A robust color image watermarking scheme in the fusion domain based on LU factorization,” Optics & Laser Technology, vol. 174, (2024), Art. no. 110567.

S.A. Kahdim and A.M. Abduldaim, “Principal component analysis for zero watermarking technique,” International Journal of Mathematics and Computer Science, vol. 18, no. 1, (2023), pp. 85-97.

X. Wang, Q. Du, L. Du, H. Zhang, and J. Hu, “Robust zero-watermarking algorithm via multi-scale feature analysis for medical images,” Journal of Information Security and Applications, vol. 89, (2025), Art. no. 103937.

M. Yang, J. Li, U.A. Bhatti, C. Shao, and Y. Chen, “Robust watermarking algorithm for medical images based on non-subsampled shearlet transform and Schur decomposition,” Computer Materials & Continua, vol. 75, no. 3, (2023), pp. 5539-5554.

M. K. Hussein, A. Alqassab, and L. T. Alkahla, “Image Classification Using Deep Learning: A Systematic Review,” Neutrosophic Optimization and Intelligent Systems*, vol. 8, (2025).

A. Paraskevas, “Extended Certainty Factors utilizing Neutrosophic Logic,” Neutrosophic Optimization and Intelligent Systems, vol. 4, (2024).

A. S. Ravindrabahadur, R. Singh, and S. N. Tiwari, “Logarithmic Ratio-Type Estimator for Finite Population Mean under Neutrosophic Framework,” Neutrosophic Optimization and Intelligent Systems, vol. 7, (2025).

M. Al-Haj, “A Zero-Watermarking Scheme using Discrete Wavelet Transform,” Procedia Computer Science, vol. 65, (2015), pp. 1–8.

A. Alzahrani, “Enhanced Invisibility and Robustness of Digital Image Watermarking Based on DWT-SVD,” Applied Bionics and Biomechanics, vol. 2022, Art. no. 5271600, 2022.

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Published

2026-06-28

How to Cite

Kadhim Abdali, H., Areej M. Abduldaima, & E. Abdulmunim, M. (2026). Neutrosophic Domain for Image Zero Watermarking: Neutrosophic Domain for Image Zero Watermarking. Journal of Al-Qadisiyah for Computer Science and Mathematics, 18(2), Comp 460–476. https://doi.org/10.29304/jqcsm.2026.18.22948

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Section

Computer Articles