Abstract
This paper presents an image watermarking method based on fuzzy image filter. In the embedding process, a unique Gaussian noise-like watermark is added into the blue color component from the RGB color space of original image. The value of each embedding bit is secured by the use of a secret key-based stream cipher. In the extraction process, a blind detection approach is used so that the original image is not required. The decreasing weight fuzzy filter with moving average value (DWMAV) is considered and applied to the watermarked component to remove the added watermark so that the original blue color component can be estimated. The extracted watermark is finally obtained by subtracting the estimated blue color component from the watermarked one. For performance comparison purpose, the weighted Peak Signal-to-Noise Ratio (wPSNR) is used for evaluating the quality of watermarked image, the normal correlation (NC) for the accuracy of extracted watermark, and the Stirmark benchmark for the robustness of embedded watermark. Experimental results confirm superiority of the proposed watermarking method compared to the two similar previous methods.
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References
Lee, S.J., Tung, S.H.: A survey of watermarking techniques applied to multimedia. In: IEEE International Symposium on Industrial Electronics, Pusan, South Korea, pp. 272–277 (2001)
Cox, I.J., Miller, M.L., Bloom, JA.: Digital Watermarking and Steganography. Morgan Kaufmann Publishers, San Franciso (2002)
Ville, D.V.D., Nachtegael, M., Weken, D.V.D., Kerre, E.E., Philips, W., Lemahieu, I.: Noise reduction by fuzzy image filtering. IEEE Trans. Fuzzy Syst. 11(4), 429–436 (2003)
Kwan, H.K.: Fuzzy filters for noisy image filtering. In: International Symposium on Circuits and Systems, Bangkok, Thailand (2003)
Marudhachalam, R., Ilango, G.: Fuzzy hybrid filtering techniques for removal of random noise from medical images. Int. J. Comput. Appl. 38(1), 15–18 (2012)
Rahman, T., Haque, M.R., Rozario, L.J., Uddin, M.S.: Gaussian noise reduction in digital images using a modified fuzzy filter. In: 17th International Conference on Computer and Information Technology, Dhaka, pp. 217–222 (2014)
Sridevi, T., Fatima, S.S.: Digital image watermarking using genetic algorithm in DWT and SVD transform. In: 3rd International Conference on Computational Intelligence and Information Technology, pp. 485–490 (2013)
Rosiyadi, D., Lestriandoko, N.H., Fryantoni, D.: A strong sensitivity of digital image watermarking scheme for noise disturbance. In: 2nd International Conference on Technology, Informatics, Management, Engineering & Environment 2014, Bandung, pp. 7–9 (2014)
Bansal, D., Mathuria, M.: Color image dual watermarking using DCT and DWT combine approach. In: International Conference on Trends in Electronics and Informatics, Tirunelveli, pp. 630–634 (2017)
Hurrah, N.N., Loan, N.A., Parah, S.A., Sheikh, J.A.: A transform domain based robust color image watermarking scheme for single and dual attacks. In: 4th International Conference on Image Information Processing, Shimla, India, pp. 1–5 (2017)
Sudibyo, U., Eranisa, F., Rachmawanto, E.H., Setiadi, D.R.I.M., Sari, C.A.: A secure image watermarking using chinese remainder theorem based on haar wavelet transform. In: 4th International Conference on Information Technology, Computer, and Electrical Engineering, Semarang, pp. 208–212 (2017)
Thongkor, K., Supasirisun, P., Amornraksa, T.: Digital image watermarking based on regularized filter. In: 14th IAPR International Conference on Machine Vision Applications, Tokyo (2015)
Lai, C.H., Wu, J.L.: Robust image watermarking against local geometric attacks using multiscale block matching method. J. Vis. Commun. Image Represent. 20(6), 377–388 (2009)
Russo, F.: Nonlinear fuzzy filters: an overview. In: 8th European Signal Processing Conference, Trieste, Italy, pp. 1–4 (1996)
Amornraksa, T., Janthawongwilai, K.: Enhanced images watermarking based on amplitude modulation. Image Vis. Comput. 24(2), 111–119 (2006)
Petitcolas, F.: Watermarking schemes evaluation. IEEE Signal Process. Mag. 17(5), 58–64 (2000)
Abdel-Aziz, B., Chouinard, J.-Y.: On perceptual quality of watermarked images – an experimental approach. In: Kalker, T., Cox, I., Ro, Y.M. (eds.) IWDW 2003. LNCS, vol. 2939, pp. 277–288. Springer, Heidelberg (2004)
Yaghmaee, F., Jamzad, M.: Estimating watermarking capacity in gray scale images based on image complexity. EURASIP J. Adv. Signal Process. 2010(8), 1–9 (2010)
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Ula, K.M.S., Pramoun, T., Toomnark, S., Amornraksa, T. (2019). Digital Image Watermarking Based on Fuzzy Image Filter. In: Unger, H., Sodsee, S., Meesad, P. (eds) Recent Advances in Information and Communication Technology 2018. IC2IT 2018. Advances in Intelligent Systems and Computing, vol 769. Springer, Cham. https://doi.org/10.1007/978-3-319-93692-5_16
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DOI: https://doi.org/10.1007/978-3-319-93692-5_16
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