# A Robust and Secure Watermarking Approach Based on Hermite Transform and SVD-DCT
## 2 Related Work  
There are many methods for watermarking images presented in the literature, and depending on the application, the requirements of the methodologies vary. The algorithms designed for watermarking have advantages and disadvantages. The most-representative work is in the transformation domain. For example, in [PERSON] et al. [1], a strategy for watermarking images was introduced, which combines the Discrete Wavelet Transform (DWT), Discrete Cosine Transform, and Singular-Value Decomposition. The watermarks utilized in this approach are the users' biometrics and their signature. During the embedding process, the biometrics acts as the host image, while the signature serves as the watermark. In contrast, for a second embedding process, the resulting watermark of the first process is embedded into the primary host image. In both embedding processes, the host image undergoes decomposition using the DWT, and the watermark is inserted inside the low-frequency coefficient by means of SVD. In [2], [PERSON] et al. preserved medical records by incorporating them into Magnetic Resonance Imaging (MRI) patient scans. The authors used the Advanced Encryption Standard (AES) to secure the medical records and SVD to compress the MRI scan reports. Then, the DCT was applied to embed the encrypted medical health record over the compressed MRI scan. [PERSON] et al. [3] presented a combined approach for watermarking images using a resilient watermark (frequency domain) through the DWT and DCT and a fragile watermark (spatial domain). In the robust watermark, the Fisher-Yates shuffle method was used to scramble the watermark, and the LH and HL sub-bands were used to embed the watermark. On the other hand, a bitwise approach was used for the fragile watermark, including a halftoning operation in conjugation with the XOR and concatenation operations. In addition, a fragile watermarking method was used to perceive and locate the manipulated regions through the XOR operator in the extraction stage. [PERSON] [4] proposed a fragile-watermarking-based approach using the DWT, DCT, and SVD techniques. The watermark was inserted into the low-frequency coefficient of the DWT using the Quantization Index Modulation (QIM) technique, and the feature coefficients were adjusted using the Gram-Schmidt procedure. Besides, a tamper detection process under different attacks was incorporated. In [5], [PERSON] et al. introduced an encryption/watermarking algorithm using the Fractional Fourier Transform (FRFT) in a hybrid domain. The Redistributed Invariant Wavelet Transform (RIDWT) and Discrete Cosine Transform (DCT) were applied to the enlarged host image. The resulting low-frequency and high-frequency components underwent SVD, and the watermark image was subjected to double-encryption using the Arnold Transform (AT). To achieve adaptive embedding, multi-parameter Particle Swarm Optimization (PSO) was utilized. [PERSON] et al. [6] reported a frequency-domain-based approach using the DWT and DCT and applying a two-level singular-value decomposition and a three-dimensional discrete hyper-chaotic map. The HH sub-band of the DWT was used to incorporate the watermark, which contains some image parameters, and it was encrypted through the Rivest-Shamir-Adleman (RSA), AT, and SHA-1 techniques. [PERSON] and [PERSON] [7] investigated the robustness of popular image watermarking schemes using combinations of the DCT, DWT, and SVD, as well as their hybrid variations. These approaches were evaluated against traditional image-processing attacks and an adversarial attack utilizing a Deep Convolutional Neural Network (CNN) and an Autoencoder (CAE) technique. In [8], [PERSON] and [PERSON] analyzed various watermarking techniques to test robustness, imperceptibility, security, capacity, transparency, computational cost, and the false positive rate.