## 2 Conspectus of Watermarking Technology
### Watermarking Techniques Classification  
Watermarking technology is the most basic application used for copyright protection of digital content such as (color) images [35], video [36] and 3D mesh [37]. That is, the ownership information of the watermark is exploited for identifying copyright ownership and preventing fraud and theft of digital content. In fact, marked digital images can prove ownership when someone claims it by a legitimate owner. In addition, authentication is another watermarking application that aims to verify the integrity of the watermarked digital images and detect attempts to alter the original images. These watermarks are designed to be subject to signal manipulation and are used to indicate the authenticity of digital content.  
Watermarking technology can be divided according to several perspectives. First, according to human perception, it is divided into two types: visible watermarking technology and invisible technology. The former means that the watermark is visible from digital images, and the latter means that the watermark cannot be recognized by the human eye. Second, watermarking technology is divided into non-blind and blind, depending on whether the original image is needed for watermark recovery. In the non-blind technique, both the original image and watermark are required during the authentication of the watermark. The blind technique does not require a watermark or original image. Third, it is divided into a spatial domain and a frequency domain based on the work area. The former is done by directly manipulating the pixel values in the original image. The merit of the work based on the spatial domain is its simple implementation and low computational complexity, while its demerit is its weak robustness to compression. In the latter case, you need to convert the host image to an appropriate frequency working domain. Then, the coefficient is adjusted according to the values of a watermark. In general, domain transformation techniques are Discrete Cosine Transform (DCT), Singular Value Decomposition (SVD), and Discrete Wavelet Transform (DWT) [18; 38; 39]. The frequency domain-based approach is more resilient to compression attacks and image conversion attacks [36].  
Fourth, depending on whether the watermark can withstand various attacks, it is classified into a strong watermark, a fragile watermark or a semi-fragile watermark. The strong watermark-based method provides the performance to withstand compression and various image manipulations. To do this, it is characterized by converting the image into the frequency domain. The fragile watermark-based method is vulnerable to image compression and image processing, so the use of this method may be different. This is because the hidden information cannot be restored even with trivial image processing. The semi-fragile watermark-based method provides selective robustness for specific manipulations.  
There are two ways to watermark a color image in the conversion domain. The first uses gray level techniques to process each channel individually, and the second treats each pixel in the color image into a quaternion vector to which the transformation is applied.