Audio watermarking technique based on Arnold transform

ABSTRAKPenelitian ini mengembangkan teknik Compressive Sensing (CS) untuk audio watermarking dengan metode Lifting Wavelet Transform (LWT) dan Quantization Index Modulation (QIM). LWT adalah salah satu teknik mendekomposisi sinyal menjadi 2 sub-band, yaitu sub-band low dan high. QIM adalah suatu metode yang efisien secara komputasi atau perhitungan watermarking dengan menggunakan informasi tambahan. Audio watermarking dilakukan menggunakan file audio dengan format *.wav berdurasi 10 detik dan menggunakan 4 genre musik, yaitu pop, classic, rock, dan metal. Watermark yang disisipkan berupa citra hitam putih dengan format *.bmp yang masing-masing berukuran 32x32 dan 64x64 pixel. Pengujian dilakukan dengan mengukur nilai SNR, ODG, BER, dan PSNR. Audio yang telah disisipkan watermark, diuji ketahanannya dengan diberikan 7 macam serangan berupa LPF, BPF, HPF, MP3 compression, noise, dan echo. Penelitian ini memiliki hasil optimal dengan nilai SNR 85,32 dB, ODG -8,34x10-11, BER 0, dan PSNR ∞.Kata kunci: Audio watermarking, QIM, LWT, Compressive Sensing. ABSTRACTThis research developed Compressive Sensing (CS) technique for audio watermarking using Wavelet Transform (LWT) and Quantization Index Modulation (QIM) methods. LWT is one technique to decompose the signal into 2 sub-bands, namely sub-band low and high. QIM is a computationally efficient method or watermarking calculation using additional information. Audio watermarking was done using audio files with *.wav format duration of 10 seconds and used 4 genres of music, namely pop, classic, rock, and metal. Watermark was inserted in the form of black and white image with *.bmp format each measuring 32x32 and 64x64 pixels. The test was done by measuring the value of SNR, ODG, BER, and PSNR. Audio that had been inserted watermark was tested its durability with given 7 kinds of attacks such as LPF, BPF, HPF, MP3 Compression, Noise, and Echo. This research had optimal result with SNR value of 85.32 dB, ODG value of -8.34x10-11, BER value of 0, and PSNR value of ∞.Keywords: Audio watermarking, QIM, LWT, Compressive Sensing.

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Robust Audio Watermarking Based On Hybrid Transformation For Copyright Protection

10.34279/0923-008-004-007 ◽

2018 ◽

pp. 39

Author(s):

Matheel E. Abdulmunem ◽

Ameer A. Badr

Keyword(s):

Copyright Protection ◽

Audio Watermarking

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Audio Watermarking Algorithm Against Synchronization Attacks Based on

ACTA AUTOMATICA SINICA ◽

10.3724/sp.j.1004.2013.01321 ◽

2014 ◽

Vol 39 (8) ◽

pp. 1321-1329 ◽

Cited By ~ 1

Author(s):

Xiong-Hua HUANG ◽

Hong-Xia WANG ◽

Wei-Zhen JIANG ◽

Geng-Shen CUI

Keyword(s):

Audio Watermarking

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Image encryption based on Fractional wavelet transform, Arnold transform with the double random phases in HSV color domain

Recent Advances in Computer Science and Communications ◽

10.2174/2666255813999200918123535 ◽

2020 ◽

Vol 13 ◽

Author(s):

Aarushi Shrivastava ◽

Janki Ballabh Sharma ◽

Sunil Dutt Purohit

Keyword(s):

Wavelet Transform ◽

Image Encryption ◽

Fractional Fourier Transform ◽

Color Image ◽

Random Phase ◽

Arnold Transform ◽

Time Frequency ◽

Key Space ◽

Secret Keys ◽

Fractional Wavelet Transform

Objective: In the recent multimedia technology images play an integral role in communication. Here in this paper, we propose a new color image encryption method using FWT (Fractional Wavelet transform), double random phases and Arnold transform in HSV color domain. Methods: Firstly the image is changed into the HSV domain and the encoding is done using the FWT which is the combination of the fractional Fourier transform with wavelet transform and the two random phase masks are used in the double random phase encoding. In this one inverse DWT is taken at the end in order to obtain the encrypted image. To scramble the matrices the Arnold transform is used with different iterative values. The fractional order of FRFT, the wavelet family and the iterative numbers of Arnold transform are used as various secret keys in order to enhance the level of security of the proposed method. Results: The performance of the scheme is analyzed through its PSNR and SSIM values, key space, entropy, statistical analysis which demonstrates its effectiveness and feasibility of the proposed technique. Stimulation result verifies its robustness in comparison to nearby schemes. Conclusion: This method develops the better security, enlarged and sensitive key space with improved PSNR and SSIM. FWT reflecting time frequency information adds on to its flexibility with additional variables and making it more suitable for secure transmission.

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