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Advances in Audio Watermarking Based on Matrix Decomposition

  • Pranab Kumar Dhar
  • Tetsuya Shimamura
Book
  • 508 Downloads

Part of the SpringerBriefs in Speech Technology book series (BRIEFSSPEECHTECH)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Pranab Kumar Dhar, Tetsuya Shimamura
    Pages 1-9
  3. Pranab Kumar Dhar, Tetsuya Shimamura
    Pages 11-22
  4. Pranab Kumar Dhar, Tetsuya Shimamura
    Pages 23-31
  5. Pranab Kumar Dhar, Tetsuya Shimamura
    Pages 33-41
  6. Pranab Kumar Dhar, Tetsuya Shimamura
    Pages 43-51
  7. Pranab Kumar Dhar, Tetsuya Shimamura
    Pages 53-54
  8. Back Matter
    Pages 55-56

About this book

Introduction

This book introduces audio watermarking methods in transform domain based on matrix decomposition for copyright protection. Chapter 1 discusses the application and properties of digital watermarking. Chapter 2 proposes a blind lifting wavelet transform (LWT) based watermarking method using fast Walsh Hadamard transform (FWHT) and singular value decomposition (SVD) for audio copyright protection. Chapter 3 presents a blind audio watermarking method based on LWT and QR decomposition (QRD) for audio copyright protection. Chapter 4 introduces an audio watermarking algorithm based on FWHT and LU decomposition (LUD). Chapter 5 proposes an audio watermarking method based on LWT and Schur decomposition (SD). Chapter 6 explains in details on the challenges and future trends of audio watermarking in various application areas.

  • Introduces audio watermarking methods for copyright protection and ownership protection;
  • Describes watermarking methods with encryption and decryption that provide excellent performance in terms of imperceptibility, robustness, and data payload;
  • Discusses in details on the challenges and future research direction of audio watermarking in various application areas.


Keywords

Lifting wavelet transform (LWT) Singular value decomposition (SVD) Signal-to-noise ratio (SNR) Mean opinion score (MOS) Subjective difference grade (SDG) Objective difference grade (ODG) Normalized correlation (NC) Bit error rate (BER) False positive error (FPE) False negative error (FNE)

Authors and affiliations

  • Pranab Kumar Dhar
    • 1
  • Tetsuya Shimamura
    • 2
  1. 1.Department of Computer Science and EngineeringChittagong University of Engineering and Technology (CUET)ChittagongBangladesh
  2. 2.Graduate School of Science and EngineeringSaitama UniversitySaitamaJapan

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-15726-5
  • Copyright Information The Author(s), under exclusive license to Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-030-15725-8
  • Online ISBN 978-3-030-15726-5
  • Series Print ISSN 2191-737X
  • Series Online ISSN 2191-7388
  • Buy this book on publisher's site
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