相关论文: Object-level Copy-Move Forgery Image Detection bas…

Copy-move forgery detection is a crucial research area within digital image forensics, as it focuses on identifying instances where objects in an image are duplicated and placed in different locations. The detection of such forgeries is…

Image forensics has become increasingly crucial in our daily lives. Among various types of forgeries, copy-move forgery detection has received considerable attention within the academic community. Keypoint-based algorithms, particularly…

With increasing revelations of academic fraud, detecting forged experimental images in the biomedical field has become a public concern. The challenge lies in the fact that copy-move targets can include background tissue, small foreground…

Realistic image forgeries involve a combination of splicing, resampling, cloning, region removal and other methods. While resampling detection algorithms are effective in detecting splicing and resampling, copy-move detection algorithms…

We propose a method to identify the source and target regions of a copy-move forgery so allow a correct localisation of the tampered area. First, we cast the problem into a hypothesis testing framework whose goal is to decide which region…

Copy-move forgery is a manipulation of copying and pasting specific patches from and to an image, with potentially illegal or unethical uses. Recent advances in the forensic methods for copy-move forgery have shown increasing success in…

The recently developed deep algorithms achieve promising progress in the field of image copy-move forgery detection (CMFD). However, they have limited generalizability in some practical scenarios, where the copy-move objects may not appear…

A copy-move forgery is created by copying and pasting content within the same image, and potentially post-processing it. In recent years, the detection of copy-move forgeries has become one of the most actively researched topics in blind…

Recent advances in deep learning algorithms have shown impressive progress in image copy-move forgery detection (CMFD). However, these algorithms lack generalizability in practical scenarios where the copied regions are not present in the…

In this work, we present a learning based method focusing on the convolutional neural network (CNN) architecture to detect these forgeries. We consider the detection of both copy-move forgeries and inpainting based forgeries. For these, we…

Since images are used as evidence in many cases, validation of digital images is essential. Copy-move forgery is a special kind of manipulation in which some parts of an image is copied and pasted into another part of the same image.…

Image copy-move is an operation that replaces one part of the image with another part of the same image, which can be used for illegal purposes due to the potential semantic changes. Recent studies have shown that keypoint-based algorithms…

Copy-move image forgery aims to duplicate certain objects or to hide specific contents with copy-move operations, which can be achieved by a sequence of manual manipulations as well as up-to-date deep generative network-based swapping. Its…

In this contemporary world digital media such as videos and images behave as an active medium to carry valuable information across the globe on all fronts. However there are several techniques evolved to tamper the image which has made…

In the current era, image manipulation is becoming increasingly easier, yielding more natural looking images, owing to the modern tools in image processing and computer vision techniques. The task of the segregation of forged images has…

Detecting reliably copy-move forgeries is difficult because images do contain similar objects. The question is: how to discard natural image self-similarities while still detecting copy-moved parts as being "unnaturally similar"? Copy-move…

With rapid advances in digital information processing systems, and more specifically in digital image processing software, there is a widespread development of advanced tools and techniques for digital image forgery. One of the techniques…

In this paper, a copy-move forgery detection method based on Convolutional Kernel Network is proposed. Different from methods based on conventional hand-crafted features, Convolutional Kernel Network is a kind of data-driven local…

Copy-move forgery is the most popular and simplest image manipulation method. In this type of forgery, an area from the image copied, then after post processing such as rotation and scaling, placed on the destination. The goal of Copy-move…

Recent advances in image editing techniques have posed serious challenges to the trustworthiness of multimedia data, which drives the research of image tampering detection. In this paper, we propose ObjectFormer to detect and localize image…