###### Abstract  
Image watermarking is most often used to prove that an image belongs to someone and to make sure that the image is the same as was originally produced. The type of watermarking used for the detection of originality and tampering is known as authentication-type watermarking. In this paper, a blind semi-fragile authentication watermarking method is introduced. Although the main concern in this paper is authenticating the image, watermarking for proving ownership is additionally implemented. The method considers the image as two main parts: an inner part and an outer part. The inner and outer parts are divided into non-overlapping blocks. The block size of the inner and outer part are different. The outer blocks have a greater area than the inner blocks so that their watermark-holding capacity is greater, providing enough robustness for semi-fragility. The method is semi-fragile and the watermarked image is authenticated despite the JPEG being compressed to 75% quality. The embedded watermark also survives innocent types of image operations, such as intensity adjustment, histogram equalization and gamma correction. Semi-fragile and selectively fragile authentication is valuable and in high demand specifically because it survives these innocent image operations while detecting ill-intentioned tampering. In this work, we embed a binary watermark into the inner and outer parts of images using a scrambling algorithm, discrete wavelet transform (DWT) and discrete cosine transform (DCT) in the blocks. The proposed methodology has high image quality after watermarking, with a PSNR value of 40.577, and high quality is also achieved after JPEG compression. The embedding process provides acceptable image quality after tamper attacks, including JPEG compression, Gaussian noise, average filtering, and scaling attacks with PSNR values greater than 29. Experimental results obtained show that the proposed semi-fragile watermarking algorithm is more robust, secure and resistant than other algorithms in the literature. m 20231200510 10 January 20231200510  
embedded message. Semi-blind watermarking uses a watermark logo and watermarked image, while blind watermarking uses a secret key only to find the embedded watermark. Image watermarking is mainly used to prove that an image belongs to someone; that the image in question relates to the sender who sent it. There are also other uses of watermarking, such as advertisement tracking, transaction tracking, and metadata storage [1]. Image watermarking involves embedding data into an image in a way that it will not be possible to see or remove the watermark from the image without destroying the overall appearance of the image. Although, generally, it is apparent that the image contains a watermark, it must not be seen or extracted without the key and the relevant method. Watermarking methods aim to prove ownership. The embedded watermark must survive common image operations, such as Lossy compression, format change, filtering, cropping, rotation, or resizing. This property is known as the robustness of the method. The algorithm must also be robust against damaging operations, such as rotation, cropping and re-watermarking [1; 2; 3]. It is also desired for the watermarked image to resemble the original image as much as possible. This property is called the fidelity of the method. Fidelity is measured as the peak signal-to-noise ratio (PSNR) value as given in Equation [1]. The rounded mean square error (RMSE) is measured between two images as in Equation [2] where I is the original image and I* is the watermarked image, and i, j are the pixel coordinates. There is always a trade-off between robustness and fidelity. When robustness increases, fidelity decreases. \[\text{PSNR}=20\log_{10}(255/\text{RMSE}) \tag{1}\]  
\[\text{RMSE}=\text{sqrt}\bigg{(}\bigg{(}\sum_{ij}\left(I_{ij}^{*}-I_{ij} \right)^{2}\bigg{)}\bigg{)}/(NxN) \tag{2}\]  
Another type of watermarking is authentication purpose watermarking.