Robust Image Data Hiding Technique for Copyright Protection

Introduction

The development in transmission technology and Internet has greatly simplified sharing, copying and distribution of digital data. However, this poses serious challenges to authentication and copyright ownership. Digital data hiding (Fredrick, 2010; Hopper et al., 2002; Cheddad et al., 2010) is one of the widely used techniques to ensure authentication and rightful ownership. It involves embedding of a copyright mark in the original content which is later extracted and used for authentication. An effective data hiding scheme for copyright protection should be capable of hiding the secret data not only imperceptibly but also in a robust manner so that the secrecy of the embedded data is maintained and it remains detectable regardless of geometrical (rotation, scaling, etc.) and signal processing attacks like filtering, compression, transformation, noise contamination. Thus, robustness against various attacks and imperceptibility are the key features of any data hiding technique used for digital image authentication and copyright protection.

The data hiding techniques are broadly classified into spatial domain and transform domain techniques. The spatial domain techniques are computationally simple and straight forward but are more fragile to external attacks and, therefore, less robust. In transform domain techniques, the host data is first transformed into frequency domain using transforms like Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) and then the secret data is embedded in significant areas. Transform domain techniques require more computations than spatial domain techniques but are more robust against common image processing operations such as existing image compression standards, low-pass filtering, cropping, addition of noise, etc. Hence, they are gaining much attention these days.

In this paper, we propose a robust image data hiding technique for copyright protection. Our scheme uses spread spectrum technique to embed secret data into singular values of middle frequency sub-bands of Redundant Discrete Wavelet Transform (RDWT) coefficients of the cover image. Spread spectrum technique is widely used in data hiding to achieve robustness against forced removal of hidden data (Cox et al., 1997). We use middle frequency sub-band for embedding because they are likely to survive normal processing and data can be embedded in them imperceptibly.

One of the early work done in transform domain data hiding was by Cox et.al.(1997) which uses spread spectrum technology to insert a Gaussian random vector in perceptually most significant spectral components of the data to identify owner. Other reported works that are closely related to our work include (Makbol & Khoo, 2013; Rastegar et al., 2013; Bhatnagar & Raman 2009; Wang & Chen, 2009; Ganic & Eskicioglu, 2005; Mohammad & Shaltaf, 2008; Liu & Tan, 2002; Singh & Siddiqui, 2012). Makbol and Khoo (2013) proposed an image watermarking based on RDWT and singular value decomposition (SVD) for copyright protection and ownership proof. The gray scale image watermark was directly embedded into singular value of RDWT sub band of the cover image. Their scheme provided large capacity and high imperceptibility. Rastegar et al. (2011) proposed a hybrid watermarking scheme based on finite radon transform (FRAT), wavelet transform and SVD for identification and authentication. They modified the singular values of all the frequency band of the cover image with the singular values of the watermark. Bhatnagar and Raman (2009) proposed a semi- blind reference watermarking scheme based on discrete wavelet transform (DWT) and SVD for copyright protection and authenticity. A reference image obtained from directive contrast and wavelet coefficients of high frequency information of the cover image was used for watermark embedding. The use of reference image for watermark extraction provides increased security and robustness. Wang and Chen (2009) proposed a hybrid DWT-SVD copyright protection scheme based on K-mean clustering and visual cryptography. They extracted image features of the cover image by applying the DWT and SVD and classified features into two clusters using K-means clustering. Ganic and Eskicioglu (2005) proposed a hybrid non-blind scheme based on SVD and DWT for copyright protection. Their scheme involves modification of singular values of each band of the cover image with the singular values of the watermark.