Multiple Watermarking Citra Menggunakan Integer Wavelet Transform (Iwt) Dan Singular Value Decomposition (Svd) Berdasarkan Human Visual Characteristics

• CHAIRUL FIKRI
• 14210125

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ABSTRAK

ABSTRAK

Nama : Chairul Fikri

Program Studi : Ilmu Komputer

Fakultas : Teknologi Informasi

Jenjang : Strata Dua (S2)

Konsentrasi : Software Engineering

Judul : “Multiple Watermarking Citra Menggunakan Integer Wavelet Transform (Iwt) Dan Singular Value Decomposition (Svd) Berdasarkan Human Visual Characteristics”

Watermarking adalah teknik yang penting dalam melindungi hak cipta dan integritas citra digital. Penelitian sebelumnya menunjukkan ketahanan terbatas pada watermarking berbasis Discrete Wavelet Transform (DWT) karena rentan terhadap serangan pemrosesan sinyal seperti median filtering, JPEG compression, dan salt & pepper noise. Penelitian ini mengusulkan skema watermarking citra yang kuat dan aman berdasarkan karakteristik visual manusia. Metode ini menggunakan kombinasi Integer Wavelet Transform (IWT) dan Singular Value Decomposition (SVD) untuk menyisipkan beberapa watermark ke dalam citra. Penelitian ini mengusulkan nilai ambang batas untuk penyisipan kedua watermark pada warna merah dan biru. Ambang batas sebesar 0,06 dan 0,13 untuk warna merah dan biru secara berurutan diusulkan untuk mengatur kekuatan penyisipan watermark . Ambang batas ini diuji dengan melakukan iterasi satu persatu terhadap kompresi JPEG. Secara khusus, untuk citra Lena, metode yang diusulkan menunjukkan nilai Absolute Reconstruction Error (ARE) lebih kecil yaitu 1,2415 dan nilai Structural Similarity Index (SSIM) lebih tinggi yaitu 0,9158 dibandingkan dengan penelitian sebelumnya. Namun, untuk citra Airplane, metode yang diusulkan menunjukkan nilai ARE yang sedikit lebih tinggi yaitu 1,8989 dan nilai SSIM yang lebih rendah yaitu 0,8722 dibandingkan dengan penelitian sebelumnya. Pada serangan Gaussian Median Filter, metode watermarking yang diusulkan mencapai nilai NC sebesar 0,9246 dan nilai BER sebesar 0,0742 pada kanal merah. Hal ini menunjukkan bahwa metode ini memiliki ketahanan yang lebih baik dibandingkan dengan penelitian sebelumnya terhadap serangan tersebut. Total peningkatan ketahanan metode yang diusulkan dibandingkan dengan penelitian sebelumnya adalah 41,6%. Hasil eksperimen menunjukkan bahwa metode yang diusulkan mengungguli penelitian sebelumnya dalam hal tak terlihatan dan kualitas citra. Metode yang diusulkan menunjukkan ketahanan yang baik terhadap berbagai serangan, termasuk Gaussian Median Filter, Salt & pepper noise, dan kompresi JPEG pada tingkat kualitas yang berbeda (JPEG QF=50 dan JPEG QF=90).

KATA KUNCI

Watermarking,IWT,SVD,Robustness,Imperseptibilitas

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DAFTAR PUSTAKA

DAFTAR PUSTAKA

[1] A. Durafe and V. Patidar, “Development and analysis of IWT-SVD and DWT-SVD steganography using fractal cover,” J. King Saud Univ. - Comput. Inf. Sci., vol. 34, no. 7, pp. 4483–4498, 2022, doi: 10.1016/j.jksuci.2020.10.008.

[2] Y. Luo et al., “A multi-scale image watermarking based on Integer Wavelet Transform and singular value decomposition,” Expert Syst. Appl., vol. 168, 2021, doi: 10.1016/j.eswa.2020.114272.

[3] F. Ernawan and D. Ariatmanto, “Image watermarking based on Integer Wavelet Transform-Singular Value Decomposition with variance pixels,” Int. J. Electr. Comput. Eng., vol. 9, no. 3, pp. 2185–2195, 2019, doi: 10.11591/ijece.v9i3.pp2185-2195.

[4] K. R. Chetan and S. Nirmala, “An efficient and secure robust watermarking scheme for document images using Integer wavelets and block coding of binary watermark s,” J. Inf. Secur. Appl., vol. 24–25, pp. 13–24, 2015, doi: 10.1016/j.jisa.2015.07.002.

[5] L. De Lathauwer, B. De Moor, and J. Vandewalle, “A multilinear singular value decomposition,” SIAM J. Matrix Anal. Appl., vol. 21, no. 4, pp. 1253–1278, 2000, doi: 10.1137/S0895479896305696.

[6] C. C. Lai, “An improved SVD-based watermarking scheme using Human Visual Characteristics,” Opt. Commun., vol. 284, no. 4, pp. 938–944, 2011, doi: 10.1016/j.optcom.2010.10.047.

[7] L. Xiong, Z. Xu, and Y. Xu, “A multiple watermarking scheme based on orthogonal decomposition,” Multimed. Tools Appl., vol. 75, no. 10, pp. 5377–5395, 2016, doi: 10.1007/s11042-015-2504-x.

[8] N. Alias and F. Ernawan, “Multiple watermarking technique using optimal threshold,” Indones. J. Electr. Eng. Comput. Sci., vol. 18, no. 1, pp. 368– 376, 2019, doi: 10.11591/ijeecs.v18.i1.pp368-376.

[9] N. Umasankari and B. Muthukumar, “Secured ICA technique on bimodal biometric images using private watermarking with DCT,” Adv. Parallel Comput., vol. 37, pp. 28–36, 2020, doi: 10.3233/APC200115.

[10] N. T. Le, “Invisible watermarking optical camera communication and compatibility issues of IEEE 802.15.7r1 specification,” Opt. Commun., vol. 390, pp. 144–155, 2017, doi: 10.1016/j.optcom.2016.12.073.

[11] M. Saadatmorad, R. A. J. Talookolaei, M. H. Pashaei, S. Khatir, and M. A. 53 Program Studi Ilmu Komputer (S2) Universitas Nusa Mandiri Wahab, “Pearson Correlation and Discrete Wavelet Transform for Crack Identification in Steel Beams,” Mathematics, vol. 10, no. 15, 2022, doi: 10.3390/math10152689.

[12] L. Dong, Y. Zhou, and J. Jiang, “Generative synthesis of logos across DCT domain,” Neurocomputing, vol. 467, pp. 163–172, 2022, doi: 10.1016/j.neucom.2021.09.068.

[13] I. A. Ansari, M. Pant, and C. W. Ahn, “Robust and false positive free watermarking in IWT domain using SVD and ABC,” Eng. Appl. Artif. Intell., vol. 49, pp. 114–125, 2016, doi: 10.1016/j.engappai.2015.12.004.

[14] J. Wentz, J. C. Cameron, and D. M. Bortz, “ANALYTICAL SINGULAR VALUE DECOMPOSITION FOR A CLASS OF STOICHIOMETRY MATRICES,” SIAM J. Matrix Anal. Appl., vol. 43, no. 3, pp. 1109–1147, 2022, doi: 10.1137/21M1418927.

[15] F. Ernawan, S. C. Liew, Z. Mustaffa, and K. Moorthy, “A blind multiple watermark s based on Human Visual Characteristics,” Int. J. Electr. Comput. Eng., vol. 8, no. 4, pp. 2578–2587, 2018, doi: 10.11591/ijece.v8i4.pp2578-2587.

[16] F. Ernawan, M. Ramalingam, A. S. Sadiq, and Z. Mustaffa, “An improved Imperceptibility and robustness of 4×4 DCT-SVD image watermarking using modified entropy,” J. Telecommun. Electron. Comput. Eng., vol. 9, no. 2–7, pp. 111–116, 2017.

[17] A. M. Hasan, M. R. Mohebbian, K. A. Wahid, and P. Babyn, “HybridCollaborative Noise2Noise Denoiser for Low-Dose CT Images,” IEEE Trans. Radiat. Plasma Med. Sci., vol. 5, no. 2, pp. 235–244, 2021, doi: 10.1109/TRPMS.2020.3002178.

[18] A. Horé and D. Ziou, “Image quality metrics: PSNR vs. SSIM,” in Proceedings - International Conference on Pattern Recognition, 2010, pp. 2366–2369. doi: 10.1109/ICPR.2010.579.

[19] A. Kaso, “Computation of the normalized cross-correlation by fast Fourier transform,” PLoS One, vol. 13, no. 9, 2018, doi: 10.1371/journal.pone.0203434.

[20] M. Hamidi, M. El Haziti, H. Cherifi, and M. El Hassouni, “A hybrid robust image watermarking method based on dwt-dct and sift for copyright protection,” J. Imaging, vol. 7, no. 10, 2021, doi: 10.3390/jimaging7100218.

[21] M. Alam, X. Chen, Z. Zhang, Y. Li, and J. He, “A brain-machine-muscle interface for restoring hindlimb locomotion after complete spinal transection in rats,” PLoS One, vol. 9, no. 8, 2014, doi: 10.1371/journal.pone.0103764. 54 Program Studi Ilmu Komputer (S2) Universitas Nusa Mandiri

[22] G. Bhatnagar and Q. M. J. Wu, “A new robust and efficient multiple watermarking scheme,” Multimed. Tools Appl., vol. 74, no. 19, pp. 8421– 8444, 2015, doi: 10.1007/s11042-013-1681-8.

[23] N. M. Makbol, B. E. Khoo, and T. H. Rassem, “Block-based Discrete Wavelet Transform-Singular Value Decomposition image watermarking scheme using human visual system characteristics,” IET Image Process., vol. 10, no. 1, pp. 34–52, 2016, doi: 10.1049/iet-ipr.2014.0965.

[24] H. T. Hu, L. Y. Hsu, and J. Garcia-Alfaro, “Exploring DWT-SVD-DCT feature parameters for robust multiple watermarking against JPEG and JPEG2000 compression,” Comput. Electr. Eng., vol. 41, no. C, pp. 52–63, 2015, doi: 10.1016/j.compeleceng.2014.08.001.

[25] S. Fazli and M. Moeini, “A robust image watermarking method based on DWT, DCT, and SVD using a new technique for correction of main geometric Attacks,” Optik (Stuttg)., vol. 127, no. 2, pp. 964–972, 2016, doi: 10.1016/j.ijleo.2015.09.205.

[26] A. K. Singh, M. Dave, and A. Mohan, “Robust and secure multiple watermarking in wavelet domain,” J. Med. Imaging Heal. Informatics, vol. 5, no. 2, pp. 406–414, 2015, doi: 10.1166/jmihi.2015.1407.

[27] A. K. Singh, “Improved hybrid algorithm for robust and imperceptible multiple watermarking using digital images,” Multimed. Tools Appl., vol. 76, no. 6, pp. 8881–8900, 2017, doi: 10.1007/s11042-016-3514-z.

[28] X. Zhou, H. Zhang, and C. Wang, “A robust image watermarking technique based on DWT, APDCBT, and SVD,” Symmetry (Basel)., vol. 10, no. 3, 2018, doi: 10.3390/SYM10030077.

[29] S. Ramakrishnan and S. Ponni alias Sathya, “Video Copyright Protection Using Chaotic Maps and Singular Value Decomposition in Wavelet Domain,” IETE J. Res., vol. 66, no. 3, pp. 290–302, 2020, doi: 10.1080/03772063.2018.1496801.

[30] Y. Yuan, D. Huang, and D. Liu, “An integer wavelet based multiple logowatermarking scheme,” in First International Multi- Symposiums on Computer and Computational Sciences, IMSCCS’06, 2006, pp. 175–179. doi: 10.1109/IMSCCS.2006.252.

[31] F. Ernawan, “Robust image watermarking based on psychovisual threshold,” J. ICT Res. Appl., vol. 10, no. 3, pp. 228–242, 2016, doi: 10.5614/itbj.ict.res.appl.2016.10.3.3.