In this paper we propose an algorithmic approach for Convolutional Neural Network (CNN) for digital watermarking which outperforms the existing frequency domain techniques in all aspects including security along with the criteria in the neural networks such as conditions embedded, and types of watermarking attack. This research addresses digital watermarking in deep neural networks and…

Online handwriting is a dynamic signal that can support digital watermarking, but existing studies have mainly evaluated individual embedding methods, leaving limited structured evidence on the joint relationship between payload, distortion, robustness, and host-signal characteristics. This paper addresses this gap through a comparative framework that combines cross-dataset host-signal characterization with a controlled evaluation of representative…

Recently, digital image forgery detection is an emergent and important area of image processing. Digital image plays a vital role in providing evidence for any unusual incident. However, the image forgery my hide evidence and prevents the detection of such criminal cases due to advancement in image processing and availability of sophisticated software tamper of…