## 1 Introduction  
In recent years, the necessity to protect multimedia content from illegal copying has been made more critical by the advent of digital technology. A common and well-discussed solution to counter the unauthorized distribution of copyrighted contents is applied by means of digital watermarking. This term refers to specific information hiding techniques whose purpose is to embed secret information inside multimedia contents, such as images, video or audio streams. The watermark, i.e., the signal added to digital media, can be detected and retrieved when necessary. In the specific field of copyrighted content protection, the objective is to identify the media's owner by means of a specific user-related watermark. The majority of watermarking techniques can be categorized as algorithms operating either in the _spatial domain_ or in the _transform domain_. Examples of embedding schemes, which insert the mark in the _spatial domain_ by modifying a subset of the image pixels, are analyzed in [1-5]. Watermarking schemes operating in the _transform domain_ represent the original image in a transformed domain where the embedding is performed. They are generally more robust than those in the spatial domain, since most of the attacks can be characterized and modeled in the transform domain [6]. Common examples are methods based on the _frequency domain_, such as Discrete Cosine Transform (DCT) [7], Discrete Fourier Transform (DFT) [8] and Discrete Wavelet Transform (DWT) [9], or schemes based on the Singular Value Decomposition (SVD). The general requirement in devising a new watermarking scheme for copyright protection is to achieve a compromise between the invisibility of the hidden watermark, while maintaining a high quality of the digital media, and its robustness against common signal processing operations and specific attacks aimed at removing the watermark or making it undetectable. In recent years, different human visual models (Watson model, masking functions, etc.) have been extensively exploited to achieve such an optimal compromise [10, 11]. A watermarking algorithm is generally classified as _robust_ or _fragile_. The former is characterized by a high resistance to attacks and can be considered as one of the most interesting and widespread applications of digital watermarking. For information about the latter, the reader may refer to [12]. A further classification may be given according to evidence of ownership; indeed, watermarking schemes are generally considered _invertible_ or _non-invertible_. In fact, suppose that the original image is \(I_{o}\) and \(W\) is the watermark to be inserted; then, the embedding process is carried out by means of a function \(E\), defined as follows:  
\[I_{w}{=}E\{I_{o}\), \(W\}\),  
where \(I_{w}\) is the watermarked image. A scheme is said to be non-invertible if it is computationally unfeasible for an attacker to use the watermarked image \(I_{w}\) to construct a fake original image \(I_{oF}\) and a fake watermark \(W_{F}\) so that \(E\{I_{o}\), \(W\}=E\{I_{oF}\), \(W_{F}\}\). In addition, watermarking schemes can also be categorized in the following three classes: _non-blind methods_, which require at least the original media and, in some cases, the original watermark in the detection process; _semi-blind schemes_, which use only the original watermark or some other side information; and _blind algorithms_, which use neither the original data nor the watermark in the detection process [13]. According to the studies of [PERSON] _et al_. [14], using invisible watermarks to establish rightful ownerships requires that the original media _isn't directly used_ in the extraction process. Therefore, non-blind watermarking schemes are not suitable for proving the ownership of a digital media. In this paper we introduce a novel block-based watermarking scheme, which uses the Singular Value Decomposition transform.