Publications

Abstract : Singular Value Decomposition (SVD) became a promising approach for developing digital media watermarking techniques due to stability and higher energy packing nature of singular values. Nevertheless, SVD based watermarking techniques suffers from false positive problem (FPP) when singular vectors are shared for extraction. Eliminating FPP in the development of digital audio watermarking (DAW) is still a challenging task. In this work, SVD based schemes and their vulnerability to FPP are studied, analyzed, and elucidated in detail. Further, a false positive free SVD based DAW scheme has been devised in Integer Wavelet Transform (IWT) domain. Audio is partitioned into segments. Each audio segment is transformed using IWT and SVD is applied on Arnold transformed watermark. Principal Component (PC) is obtained with the product of singular vector matrix and singular values matrix. Transformed audio is modified based on PC of watermark image. The developed scheme has been tested on benchmark dataset and it maintains imperceptibility, robustness, and capacity as per standards. The developed scheme has achieved resilience against signal processing attacks. Consequently, this DAW scheme helps in forensic examination of audio recording for authentication purpose.