Data Adaptive Multi-Band Approach for Robust Audio Watermarking Using Adaptive Threshold

A.K.M. NAZMUS SAKIB; A K M Wasif Abedin; Mahfuza Khatun

Data Adaptive Multi-Band Approach for Robust Audio Watermarking Using Adaptive Threshold

A.K.M. Nazmus Sakib * § B.Sc.

Contact

A K M Wasif Abedin §

Contact

Mahfuza Khatun §

Contact

tareq.mhd §

Contact

pramanikanis §

Contact

§ Dhaka International University

Data Adaptive Multi-Band Approach for Robust Audio Watermarking Using Adaptive Threshold

Article Fingerprint

ReserarchID

CSTGV6754O

Data Adaptive Multi-Band Approach for Robust Audio Watermarking Using Adaptive Threshold Banner

Key Research Insights

Synthesized scholarly intelligence & interactive research assistant

This converted HTML version may contain rendering inconsistencies. Please refer to the PDF for the authoritative version, or click here to provide feedback.

Abstract

This paper presents a data adaptive digital audio watermarking process with the use of Empirical Mode Decomposition (EMD) and Hilbert Transform (HT). The host audio signal is decomposed into several Intrinsic Mode Functions (IMFs). A binary image or a set of -1 and 1, which is obtained by mapping from standard normal distributed pseudo random numbers, is embedded as secret information into the significant coefficients of the highest energetic IMF that are greater than a specified adaptive threshold. Thus watermarked IMF is less sensitive to common signal processing attack. As a result this method increases more robustness. The experimental results show that the proposed method has good imperceptibility and robustness under common signal processing attacks such as additive noise (in time domain and in frequency domain), low pass filtering, re-sampling, re-quantization, MP3 compression, and sound processing effects such as, delay, a natural sounding reverberation (Schroeder’s Reverberator), flanging effect, equalization effect, etc. A Bit Error calculation equation is provided to measure the accuracy of the extracted watermark.

References

7 Cites in Article

Reference Format

1. Ahmet Eskicioglu,Edward Delp (2001). An overview of multimedia content protection in consumer electronics devices. Signal Processing: Image Communication, 16(7), 681-699.
2. A Eskicioglu,E Delp (2003). Security of Digital Entertainment Content From Creation to Consumption. Signal Processing : Image Communication, Special Issue on Image Security, 118(4), 237-262.
3. I Cox,M Miller,J Bloom (2002). Digital Watermarking. Digital Watermarking
4. Norden Huang,Zheng Shen,Steven Long,Manli Wu,Hsing Shih,Quanan Zheng,Nai-Chyuan Yen,Chi Tung,Henry Liu (1998). The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 454(1971), 903-995.
5. Lingfei Liang,Ziliang Ping (2008). Information Hiding Based on Empirical Mode Decomposition. IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application, 1, 561-565.
6. A Zaman,K Khalilullah,M Islam,M Molla (2010). A robust digital audio watermarking algorithm using empirical mode decomposition. Proc. of 23rd Canadian Conf. on Electrical and Computer Engineering
7. S Foo,T Yeo,D Huang (2001). An adaptive audio watermarking system. Proc. IEEE Region 10 International Conference on Electrical and Electronic Technology, 509-513.

Download References

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

A.K.M. NAZMUS SAKIB, A K M Wasif Abedin, Mahfuza Khatun, tareq.mhd, pramanikanis. 2026. "Data Adaptive Multi-Band Approach for Robust Audio Watermarking Using Adaptive Threshold". Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 13 (GJCST Volume 13 Issue F3).

More Citation Formats

Select Citation Style:

Download Citation

GJCST Volume 13 Issue F3

Explore Journals Explore Volume Read This Issue

Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

adaptive threshold audio watermarking binary image Empirical Mode Decomposition hilbert transform wavelet transform

Classification

GJCST-F Classification I.4.5

Submission ReceivedDecember 15, 2012
Peer Review Double Blind
Handling Editor
Accepted January 1, 2013
Published January 15, 2013

Version of record

v1.2

Language

English

Order Article Reprint

Experience in AR

Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.

View in VR

Read in 3D

Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.

View in 3D

Article Matrices

Total Score: 105

Country: Bangladesh

Subject: Global Journal of Computer Science and Technology - F: Graphics & Vision

Authors: K. M. Ibrahim Khalilullah, A K M Wasif Abedin, Mahfuza Khatun, Mohammad Tareq, Md. A. R. Pramanik (PhD/Dr. count: 0)

View Count (all-time): 519

Total Views (Real + Logic): 9379

Total Downloads (simulated): 605

Publish Date: 2013 01, Tue

Monthly Totals (Real + Logic):

Month 1: 32 views
Month 2: 36 views
Month 3: 31 views
Month 4: 42 views
Month 5: 22 views
Month 6: 37 views
Month 7: 40 views
Month 8: 40 views
Month 9: 41 views
Month 10: 47 views
Month 11: 45 views
Month 12: 22 views
Month 13: 31 views
Month 14: 34 views
Month 15: 20 views
Month 16: 36 views
Month 17: 35 views
Month 18: 35 views
Month 19: 20 views
Month 20: 38 views
Month 21: 27 views
Month 22: 26 views
Month 23: 32 views
Month 24: 20 views
Month 25: 25 views
Month 26: 25 views
Month 27: 20 views
Month 28: 31 views
Month 29: 36 views
Month 30: 29 views
Month 31: 30 views
Month 32: 38 views
Month 33: 28 views
Month 34: 31 views
Month 35: 27 views
Month 36: 26 views
Month 37: 23 views
Month 38: 28 views
Month 39: 25 views
Month 40: 12 views
Month 41: 31 views
Month 42: 40 views
Month 43: 46 views
Month 44: 30 views
Month 45: 25 views
Month 46: 44 views
Month 47: 31 views
Month 48: 40 views
Month 49: 29 views
Month 50: 49 views
Month 51: 31 views
Month 52: 36 views
Month 53: 21 views
Month 54: 30 views
Month 55: 12 views
Month 56: 17 views
Month 57: 49 views
Month 58: 22 views
Month 59: 32 views
Month 60: 37 views
Month 61: 27 views
Month 62: 27 views
Month 63: 30 views
Month 64: 19 views
Month 65: 37 views
Month 66: 44 views
Month 67: 31 views
Month 68: 43 views
Month 69: 28 views
Month 70: 37 views
Month 71: 35 views
Month 72: 41 views
Month 73: 22 views
Month 74: 31 views
Month 75: 38 views
Month 76: 12 views
Month 77: 39 views
Month 78: 21 views
Month 79: 10 views
Month 80: 26 views
Month 81: 29 views
Month 82: 35 views
Month 83: 18 views
Month 84: 21 views
Month 85: 20 views
Month 86: 26 views
Month 87: 39 views
Month 88: 21 views
Month 89: 24 views
Month 90: 40 views
Month 91: 34 views
Month 92: 36 views
Month 93: 36 views
Month 94: 20 views
Month 95: 37 views
Month 96: 23 views
Month 97: 32 views
Month 98: 37 views
Month 99: 18 views
Month 100: 25 views
Month 101: 29 views
Month 102: 33 views
Month 103: 41 views
Month 104: 34 views
Month 105: 18 views
Month 106: 12 views
Month 107: 25 views
Month 108: 21 views
Month 109: 46 views
Month 110: 38 views
Month 111: 26 views
Month 112: 36 views
Month 113: 45 views
Month 114: 19 views
Month 115: 14 views
Month 116: 11 views
Month 117: 28 views
Month 118: 17 views
Month 119: 15 views
Month 120: 44 views
Month 121: 36 views
Month 122: 31 views
Month 123: 36 views
Month 124: 21 views
Month 125: 37 views
Month 126: 35 views
Month 127: 39 views
Month 128: 32 views
Month 129: 35 views
Month 130: 42 views
Month 131: 24 views
Month 132: 18 views
Month 133: 16 views
Month 134: 41 views
Month 135: 48 views
Month 136: 44 views
Month 137: 36 views
Month 138: 21 views
Month 139: 18 views
Month 140: 36 views
Month 141: 35 views
Month 142: 29 views
Month 143: 23 views
Month 144: 28 views
Month 145: 44 views
Month 146: 38 views
Month 147: 23 views
Month 148: 50 views
Month 149: 21 views
Month 150: 47 views
Month 151: 14 views
Month 152: 37 views
Month 153: 43 views
Month 154: 16 views
Month 155: 31 views
Month 156: 29 views
Month 157: 25 views
Month 158: 36 views
Month 159: 30 views
Month 160: 38 views
Month 161: 36 views
Month 162: 43 views
Month 163: 48 views
Month 164: 44 views
Month 165: 64 views
Month 166: 69 views

Total Views: 9.4K

Total Downloads: 605

All Trends