# Robust Image Watermarking Algorithm Based on ASIFT against Geometric Attacks
## 1 Introduction
[11] introduced a fragile reversible watermarking scheme for achieving authenticity and integrity. In the field of microscopy images protection, [PERSON] et al. [12] introduced a novel watermarking scheme to embed the watermark information into the confocal microscopy image. Traditional watermarking algorithms have robustness to the common attacks, such as noise addition, filter operation, cropping, and so on. However, owing to the unique features of geometric attacks, the watermark synchronization can be destroyed, bringing about the failure in watermark extraction [13]. Thus, it is urgent to propose watermarking algorithms which have resistance to geometric attacks. In recent years, there have been many schemes proposed to solve these problems, which are based on Zernike moments [14], harmonic transform [15], feature points [16], and so on. Due to the fact that SIFT is efficient for the application obtaining the image feature and matching the two images, which makes it more suitable for watermark embedding. However, the scale-invariance feature transform (SIFT) has some advantages: firstly, the significant amount of feature points can be extracted with appropriate parameter settings; secondly, the image feature extracted by SIFT has great uniqueness, which is suitable for accurate matching; finally, SIFT features are invariant to the rotation, scaling, and translations [17], which can be applied as an efficient tool for robust watermarking to acquire the robustness to the geometric attacks. [PERSON] et al. [18] introduced to use local invariant feature for embedding the watermark into the patches of circle shapes generated by SIFT, and proposed an innovative image watermarking scheme. To deal with the watermark synchronization errors, [PERSON] et al. [19] proposed an innovative watermarking scheme based on DFT and SIFT. Based on two techniques, SIFT and DWT, [PERSON] et al. [20] presented an image watermarking scheme, performing the DWT on the SIFT areas which are selected for watermark embedding. [PERSON] and [PERSON] [21] proposed a watermarking scheme resistant to the geometric attacks based on IWT and SIFT, where SIFTis utilized on the red channels, and the feature points are extracted. Then, blue and green components are performed by IWT, and low-frequency coefficients can be extracted for watermark embedding. In [22], [PERSON] et al. introduced a robust watermarking algorithm on the basis of SIFT and DCT, where the watermark information is embedded into the specific feature region performed by DCT. In [23], based on SVD and SIFT, [PERSON] and [PERSON] proposed a robust watermarking scheme for solving the watermark synchronization problem, and SIFT is applied for watermarking resynchronization. To deal with the issue of copyright protection for depth image based rendering (DIBR) 3D images, [PERSON] et al. [24] proposed a SIFT features-based blind watermarking algorithm, where feature points are extracted from different view images. Besides, a watermark pattern selection algorithm based on feature points orientation and spread spectrum technique for watermark embedding are applied in this algorithm. In [25], [PERSON] and [PERSON] presented a SIFT-based watermarking method, which is evaluated by the information hiding criteria (IHC). The local feature regions around SIFT features are applied for scaling and rotation robustness, and two error correction algorithms are used, which are weighted majority voting (WMV) and low density parity check (LDPC) code to correct the errors of extracted watermarks. As the fast algorithm compared with SIFT, speed up robust feature (SURF) algorithm is applied into watermarking algorithm. [PERSON] and [PERSON] [26] presented a geometric-distortion resilient watermarking algorithm, using the fuzzy C-means clustering to process the feature points extracted by SURF, and extracted feature point sets are used to divide the image into triangular patches for watermark embedding. However, the traditional SIFT algorithm can match feature points under the condition of rotation and scaling.