Adaptive Quantization Index Modulation Audio Watermarking based on Fuzzy Inference System

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Author(s)

Sunita V. Dhavale 1,* Rajendra S. Deodhar 2 Debasish Pradhan 3 L.M. Patnaik 4

1. Department of Computer Science and Engineering, Defence Institute of Advanced Technology, Pune, INDIA

2. Armament Research and Development Establishment, Pashan, Pune, INDIA.

3. Department of Applied Mathematics, Defence Institute of Advanced Technology, Pune, INDIA.

4. Department of Electronics Systems Engineering, Indian Institute of Science, Bangalore, INDIA

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2014.03.01

Received: 7 Nov. 2013 / Revised: 5 Dec. 2013 / Accepted: 6 Jan. 2014 / Published: 8 Feb. 2014

Index Terms

Discrete Cosine Transform, Spectral Flux, Adaptive Audio Watermarking, Quantized Index Modulation, Fuzzy Inference

Abstract

Many of the adaptive watermarking schemes reported in the literature consider only local audio signal properties. Many schemes require complex computation along with manual parameter settings. In this paper, we propose a novel, fuzzy, adaptive audio watermarking algorithm based on both global and local audio signal properties. The algorithm performs well for dynamic range of audio signals without requiring manual initial parameter selection. Here, mean value of energy (MVE) and variance of spectral flux (VSF) of a given audio signal constitutes global components, while the energy of each audio frame acts as local component. The Quantization Index Modulation (QIM) step size Δ is made adaptive to both the global and local features. The global component automates the initial selection of Δ using the fuzzy inference system while the local component controls the variation in it based on the energy of individual audio frame. Hence Δ adaptively controls the strength of watermark to meet both the robustness and inaudibility requirements, making the system independent of audio nature. Experimental results reveal that our adaptive scheme outperforms other fixed step sized QIM schemes and adaptive schemes and is highly robust against general attacks.

Cite This Paper

Sunita V. Dhavale, Rajendra S. Deodhar, Debasish Pradhan, L.M. Patnaik,"Adaptive Quantization Index Modulation Audio Watermarking based on Fuzzy Inference System", IJIGSP, vol.6, no.3, pp.1-11, 2014. DOI: 10.5815/ijigsp.2014.03.01

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