Incorporation of Perceptually Energy-Compensated QIM into DWT-DCT Based Blind Audio Watermarking

Hu, Hwai Tsu; Chen, Szu Hong; Hsu, Ling Yuan

doi:10.1109/iih-msp.2014.191

Cited by 10 publications

(4 citation statements)

References 19 publications

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“…The method of using the cosine transform to hide data is described in [ 32 ]. The data rate of 150 bit/s was achieved, as well as resistance to lossy compression and analogue to digital conversion.…”

Section: Related Workmentioning

confidence: 99%

Synchronization of Acoustic Signals for Steganographic Transmission

Wojtuń

Piotrowski

2021

Sensors

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Steganography is a technique that makes it possible to hide additional information (payload) in the original signal (cover work). This paper focuses on hiding information in a speech signal. One of the major problems with steganographic systems is ensuring synchronization. The paper presents four new and effective mechanisms that allow achievement of synchronization on the receiving side. Three of the developed methods of synchronization operate directly on the acoustic signal, while the fourth method works in the higher layer, analyzing the structure of the decoded steganographic data stream. The results of the research concerning both the evaluation of signal quality and the effectiveness of synchronization are presented. The signal quality was assessed based on both objective and subjective methods. The conducted research confirmed the effectiveness of the developed methods of synchronization during the transmission of steganographic data in the VHF radio link and in the VoIP channel.

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Section: Related Workmentioning

confidence: 99%

Synchronization of Acoustic Signals for Steganographic Transmission

Wojtuń

Piotrowski

2021

Sensors

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“…QIM can be applied in the time domain or frequency domain. The formula of QIM embedding is shown below (Hu et al, 2014):…”

Section: 4mentioning

confidence: 99%

“…Quantization Index Modulation (QIM) is popular embedding method which was first introduced in (Chen & Wornell, 2001). In the development of audio watermarking research, QIM was developed by combining it with other transform or decomposition method, such as wavelet decomposition (Hu, Chen, & Hsu, 2014) or (Novamizanti, Budiman, & Wibowo, 2018), transformation to frequency domain (Lei, Soon, & Tan, 2013), SVD (Agradriya, Perdana, Safitri, & Novamizanti, 2017) or QR decomposition (Dhar, 2014). In recent years, researchers found that embedding watermark can also be executed in centroid location of host audio, especially in the frequency domain of audio.…”

Section: Introductionmentioning

confidence: 99%

Image Hiding on Audio Subband Based On Centroid in Frequency Domain

2019

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Audio watermarking adalah mekanisme penyembunyian data pada audio. Metode penyembunyian data yang digunakan dalam penulisan ini adalah Lifting Wavelet Transform (LWT), Fast Fourier Transform (FFT), Centroid dan Quantization Index Modulation (QIM). Langkah pertama adalah host audio tersegmentasi menjadi beberapa frame. Kemudian sub-band terpilih diubah oleh FFT dengan mengubah domain sub-band dari waktu ke frekuensi. Proses centroid digunakan untuk menemukan titik pusat frekuensi untuk lokasi penyisipan untuk mendapatkan output yang lebih stabil. Proses penyematan dilakukan dengan QIM. Kinerja watermarking oleh parameter yang disesuaikan memperoleh nilai imperceptibility dengan Signal to Noise Ratio (SNR) > 21 dB, Mean Opinion Score (MOS)> 3.8 dengan kapasitas = 86.13 bps. Selain itu, untuk sebagian besar file audio terwatermark yang diserang, metode ini tahan terhadap beberapa serangan seperti Low Pass Filter (LPF) dengan fco> 6 kHz, Band Pass Filter (BPF) dengan fco 50 Hz-6 kHz, Linear Speed Change (LSC) dan MP4 Compression dengan Bit Error Rate (BER) kurang dari 20%.

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“…Chen and Wornell in [17] described QIM theoritically and applied it firstly in audio watermarking, after then their paper was becoming the main reference for audio watermarking on QIM embedding method by many researchers. QIM is frequently used in the frequency domain of the host audio as described in [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Modified DCT-based Audio Watermarking Optimization using Genetics Algorithm

2018

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Ease process digital data information exchange impact on the increase in cases of copyright infringement. Audio watermarking is one solution in providing protection for the owner of the work. This research aims to optimize the insertion parameters on Modified Discrete Cosine Transform (M-DCT) based audio watermarking using a genetic algorithm, to produce better audio resistance. MDCT is applied after reading host audio, then embedding in MDCT domain is applied by Quantization Index Modulation (QIM) technique. Insertion within the MDCT domain is capable of generating a high imperceptible watermarked audio due to its overlapping frame system. The system is optimized using genetic algorithms to improve the value of imperceptibility and robustness in audio watermarking. In this research, the average SNR reaches 20 dB, and ODG reaches -0.062. The subjective quality testing on the system obtains an average MOS of 4.22 out of five songs tested. In addition, the system is able to withstand several attacks. The use of M-DCT in audio watermaking is capable of producing excellent imperceptibility and better watermark robustness.

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Incorporation of Perceptually Energy-Compensated QIM into DWT-DCT Based Blind Audio Watermarking

Cited by 10 publications

References 19 publications

Synchronization of Acoustic Signals for Steganographic Transmission

Synchronization of Acoustic Signals for Steganographic Transmission

Image Hiding on Audio Subband Based On Centroid in Frequency Domain

Modified DCT-based Audio Watermarking Optimization using Genetics Algorithm

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