## 1 Introduction  
Nowadays, millions of images and videos are processed and transmitted by people over the internet. Images have been used heavily as evidence in law enforcement, the courts, science and medical healthcare [1]. The availability of editing software tools makes it very easy to insert, delete, edit and modify any part of the images. Hence, it is very necessary and imperative to develop forgery detection tools to identify different kinds of malicious modifications of images [2]. Resampling, image retouching, image copy paste and splicing are the main known modifications of digital images [3]. Hence, image integrity authentication, digital signatures, hash codes, watermarking and cryptography are the basic tools which are used to detect and localize the forgeries in the digital images [4]. There are two types of image authentication techniques: active [5] and passive [6]. The active techniques use the watermarks embedded inside the image to check the integrity [7; 8; 9; 10; 11], while the passive techniques do not use any prior knowledge about the image to detect forgery [12; 13; 14; 15; 16]. Digital Watermarking has been used widely, whether in its visible or blind form. Indeed, the watermark has information on the source, destination, possession, copy management, and bargain controlling, etc. [17]. Watermarking can deliver various services, for example intellectual property protection, bargain tracking, copy handling, ownership verification, certification, forensic investigation, playback chaining, estate system improvement and database connection, and biometric protection, etc. [18; 19; 20]. Copyright protection is defined as the function of confirming the possession rights to a court against the illegitimate manipulation and usage of digital data. It can enclose data about the possessor of the thing, which can be utilized to solve disputes. Each digital thing has a unique watermark specifying the holder of the thing, which requires a very high level of strength for tracking so that holders can be detected. For copyright services, the hidden watermark is supposed to be robust to various kinds of intentional and non-intentional attacks, such that the affected content is still valid in terms of visual quality [21]. The watermarking schemes are classified either as spatial domain or transform domain techniques. In the spatial domain, the watermark is hidden by changing the pixel values of the main image. For example, the least significant bit (LSB) method is one of the well-known techniques in the spatial domain. In the transform domain, the watermark is hidden by changing the frequency coefficients of the converted image. The most frequently used methods in the transform domain are discrete cosine transform (DCT) and discrete wavelet transform (DWT), etc. [22]. Many watermarking schemes have been proposed in the last few years. In these approaches, the watermark is hidden in the image at the sender side, and then it is extracted at the receiver side to check the integrity of the image. However, such watermarking techniques produce lower-quality images, and their performance is lowered by several known attacks. Hence, visual cryptography (VC)-based watermarking techniques are proposed as an alternative to the classical watermarking approaches [23; 24]. In VC-based approaches, several shares are generated to produce the secret share that is saved into the third authority party to solve any conflicts which arise in the future. This means that there are no watermarks embedded inside the host image; instead, the watermarks are used only in the construction of the secret share at the sender side, and then they are reconstructed at the receiver side for integrity verification purposes. Hence, the VC-based watermarking schemes are regarded as a promising viable solution for image quality and robustness problems [25; 26]. VC-based watermarking approaches have been used by researchers in the past few years to protect the copyright of a single image or multiple images [23; 24; 25; 26].