# Review on Semi-Fragile Watermarking Algorithms for Content Authentication of Digital Images
## 5 Overview on Semi-fragile Watermarking Algorithms
### Unrecoverable Semi-Fragile Watermarking Algorithms
#### 5.1.1 Spatial Domain  
For semi-fragile watermarking algorithms in spatial domains, the pixels of digital images are processed directly to achieve the purpose of embedding watermarking information [10; 11; 12; 13; 14]. For example, some algorithms embed the watermarking information into the least significant bit (LSB) in the image pixels directly [11; 12]. Although the spatial domain algorithms can be implemented easily, it is difficult to balance the invisibility and robustness of the watermark. [PERSON] et al. [10] proposed an authentication algorithm combining multidimensional dither modulation with error-correction coding. By using lattice quantization, the watermarking information associated with the image content is generated by all the pixel values in the image. Then the hash function and multidimensional dither modulation are combined together to encrypt and embed these data. To gain the robustness that can protect against non-malicious distortions without raising security gaps, the algorithm can restore the errors of information bits and the hash values of these error positions in a pre-defined range by combining more complicated multidimensional quantization methods with error correction coding (ECC).  
Semi-fragile watermarks can distinguish normal image processing operations from malicious tampering, which is the reason why they are superior to fragile watermarks. In view of this, [PERSON] and [PERSON] [11] proposed a new semi-fragile watermarking algorithm, which can resist the Laplacian sharpening. The parity of the pixel values and their Laplacian sharpening results are modified to embed the watermark into the spatial domain. This algorithm can tolerate the Laplacian sharpening well. However, it shows fragility when facing the neighborhood averaging and median filter. In addition, since the proposed algorithm only modifies the LSB of pixels, the complexity of it is very low and its fidelity excellent. On the basis of [11], to achieve high robustness for normal image processing operations and good tamper localization precision, [PERSON] et al. used brightness masking, texture masking, and edge masking to advance the development of the human visual system (HVS) in the spatial domain [12]. In the paper, the watermark embedding process is achieved through adaptive LSB replacement. A kind of classification rule for image authentication is proposed, which can effectively distinguish between normal image-processing operations and malicious tampering. Under some mild modifications, the proposed algorithm has a high normalized correlation coefficient (NCC) value and the tampered areas can be located accurately.  
To improve the quality of the watermarked image and the accuracy of tampering location, [PERSON] et al. [13] proposed a new watermarking algorithm for image authentication based on the vector quantization method. The watermark in the algorithm includes a robust zero-level watermark and a semi-fragile watermark. The two are divided into two stages to complete the watermark embedding process. In the first stage, the algorithm based on the random key combined with the characteristic of indices of the vector quantization image to complete the embedding of the robust zero-level watermark, which enhances security while saving bandwidth. In the second stage, a modified index key based (MIKB) method is used to achieve semi-fragile watermark embedding. In addition, the algorithm adopts the pixel neighborhood clustering method to quantitatively analyze various attacks, thus distinguishing normal image-processing operations from malicious tampering. The algorithm has high watermarking imperceptibility and tampering localization accuracy, and the \(R_{\text{FP}}\) and \(R_{\text{FN}}\) of it are very low. Due to the poor robustness of the algorithm in spatial domains, the watermarking information may be destroyed easily.