NEURAL NETWORK BASED INSERTION OF WATERMARK INTO IMAGES AND TAMPERING DETECTION THEREOF

摘要

Systems and methods for insertion of a watermark into images and tampering detection of the watermarked images by a Convolutional Neural Network (CNN) technique. The traditional systems and methods provide for detecting the tampering of the watermarked images by simply identifying a presence of an inserted watermark into an image but none them provide for inserting a random sequence into input image(s) and then detect the tampering by classifying the input image(s) by a neural network. Embodiments of the present disclosure provide for insertion of the watermark into the input image(s) and tampering detection of the watermarked images by training a Convolutional Neural Network (CNN) 201 to classify the images as tampered or non-tampered, extracting random noise, obtaining non-classified watermarked images from the random noise, and obtaining, from the non-classified watermarked images, classified watermarked images and detecting an absence or a presence of the tampering based upon the classified watermarked images.