# Review on Semi-Fragile Watermarking Algorithms for Content Authentication of Digital Images
## 5 Overview on Semi-fragile Watermarking Algorithms
### Unrecoverable Semi-Fragile Watermarking Algorithms
#### 5.1.2 Transform Domain
To distinguish normal image-processing operations from malicious tampering, [PERSON] and [PERSON] [21] extracted the image characteristics in low-frequency regions of the wavelet domain to obtain two watermarks. One is mainly used to complete the localization of the tampered areas and the other is mainly used to distinguish the normal image processing operations and malicious tampering. Thus, an effective image selection authentication mechanism is provided. The generation and the embedding of the watermark are carried out in the image itself, and two watermark tamper evaluation functions are introduced, which can be used to achieve the purpose of distinguishing attacks. [PERSON] et al. [22] also put forward a semi-fragile watermarking algorithm that can detect and classify the tamper attacks. The algorithm is an improved algorithm based on the quantization approach in the DWT domain, which adopts the multi-scale expansion bits with adjustable watermarking location to embed the random watermarking bit sequence into the DWT low frequency sub-bands of the 2 nd DWT levels (LL\({}_{2}\), LL\({}_{\text{LHI}}\), and LL\({}_{\text{HLI}}\)). It can locate the tampered areas accurately and classify the type of the attacks. However, the algorithm has not been developed to process color images and has not been examined to deal with geometric attacks. Many of the semi-fragile watermarking algorithms based on block operations in the transform domain are susceptible to local tamper attacks. To eliminate the drawbacks of block-based algorithms, [PERSON] proposed an improved semi-fragile watermarking algorithm that can locate the tampered areas precisely by using the DWT method and permuting wavelet coefficients randomly [23]. Through the quantization, the watermarking data is embedded into DWT coefficients, and the key is embedded into wavelet coefficients of the watermark, which improves the security of the algorithm. Also, the algorithm can resist the mild-to-moderate JPEG compression. In addition, semi-fragile watermarking algorithms not only can be adopted to tamper detection and localization, but also can have other performance. [PERSON] and [PERSON] [24] put forward a semi-fragile watermarking algorithm to protect image information, which not only could detect the tampered areas in images, but also could be used to declare authentication and authorization. By using DWT, the grayscale still image is decomposed into frequency domain, and multiple, multilevel and multi-energy watermarks are embedded in the image for multi-purposes. Additionally, the use of cryptographic keys increases the security of the system. To improve the security of the watermark, [PERSON] and [PERSON] [25] proposed a semi-fragile watermarking algorithm based on singular value. The watermark in this algorithm is composed of two parts. One is the singular-value-based sequence related to the content, and the other is the private-key-based sequence that is irrelevant to the content. Then the algorithm carries out a series of exclusive-or (XOR) operations on the two parts to obtain the secure watermark. Combined with the adaptive quantization approach, the generated watermark is embedded into a \(4\times 4\) block of each approximate sub-band. The authentication system of the algorithm has three levels, containing five measures used to quantify the results of the image content authentication. In addition, after undergoing the mild-to-severe image-processing operations that make no changes to the image content, the algorithm can still detect malicious tampering and locate the tampered areas accurately. However, it cannot resist geometric attacks.