# Feature-Based Image Watermarking Algorithm Using SVD and APBT for Copyright Protection
## 1 Introduction  
Since the 1990s, information hiding technology has become a major research focus in the field of information technology. The purpose of information hiding is to embed hidden data in digital media, such as image, audio, video, and so on. With the development of related technologies, information hiding has become an independent discipline, and its coverage is also expanding. According to the purpose of hiding information and technical requirements, invisibility, robustness, undetectability, security [1], and other attributes are all distinctive features of information hiding technology. As digital media can be easily copied, altered, and illegally distributed, copyright protection of digital media has aroused increasingly widespread attention. How to protect the integrity and authenticity of digital media becomes urgent and important. Thus, digital signature [2] and digital watermarking [3] have been proposed for data hiding to solve this problem. Due to its superior performance, digital watermarking is applied as an effective method to solve the image's copyright issue. According to different functions, digital watermarking can be classified into three types, containing robust watermarking, fragile watermarking, and semi-fragile watermarking. Robust watermarking can resist all kinds of attacks and common processing, which is applied for copyright protection. Fragile watermarking is sensitive to attacks, including malicious tampering and common processing. Combining advantages of the two above watermarking methods, semi-fragile watermarking is proposed to distinguish malicious tampering from non-malicious modification with the certain ability of resisting common processing. According to the domain where the watermark is embedded, two types of digital watermarking techniques can be defined [4; 5]: spatial domainwatermarking [6], and frequency or transform domain watermarking [7]. Spatial domain methods modify the pixel value of the digital image directly to embed the watermark. The least significant bit (LSB) algorithm is the common and simplest algorithm applied in spatial watermarking schemes [8], embedding the watermark information into the LSB or multiple bit layers. Correspondingly, frequency domain methods embed the watermark information by modifying transform coefficients of the original image. Compared with spatial methods, schemes based on transforms have better imperceptibility and robustness. Discrete cosine transform (DCT), discrete wavelet transform (DWT), discrete sine transform (DST), and singular value decomposition (SVD) [9] are common transforms applied in frequency domain watermarking. Moreover, other special transforms, such as redundant DWT (RDWT) [10], fractional wavelet transform (FWT) [11], and QR decomposition [12], can be applied for better performance in some certain aspects. In recent years, these transforms are still applied widely in the watermarking field. For example, [PERSON] et al. [12] proposed a robust color video watermarking scheme based on QR decomposition and entropy analysis, embedding the watermark into the block selected by entropy analysis. The selected block is performed by DWT, Chirp-Z transform (CZT), QR decomposition, and SVD for watermark embedding. In [13], [PERSON] et al. proposed a robust watermarking with the combination of DWT and DCT. In the embedding process, the HL\({}_{2}\) sub-band coefficient is divided into 4 \(\times\) 4 blocks after decomposing the cover image by two-level DWT. Then, the DCT is performed for each block. According to the watermark bit, two pseudo-random sequences are embedded into the middle band coefficients of DCT. Besides, [PERSON] et al. [14] proposed a robust watermarking scheme based on DCT and DWT in the encrypted domain to improve the robustness, using an image splitting method to embed the watermark in the low-middle frequency coefficients. [PERSON] et al.