Results 71 to 80 of about 3,997,403 (139)

Detection of copy-move image forgery using SVD and cuckoo search algorithm

, 2018
Copy-move Copy move forgery (CMF) is one of the straightforward strategies to create forged images. To detect this kind of forgery one of the widely used method is single value decomposition (SVD).
Megha Agarwal, Abhishek Kashyap, Hariom Gupta   +2 more
core   +1 more source

A Novel RINBP-DCT-Based Copy Move Forgery Detection Method Against Post-Processing Attacks

IEEE Access
Digital images are widely used for information sharing, making them increasingly vulnerable to malicious manipulations. Among different types of image tampering, copy move forgery is one of the most common techniques, where a region of an image is ...
Bilgehan Gurunlu, Serkan Ozturk
doaj   +1 more source

Biorthogonal wavelet transform-based adaptive segmentation and statistical keypoint matching approach for image forgery detection

ETRI Journal
Detecting copy–move forgeries in digital images, especially those with smooth, small, and geometrically distorted regions, remains challenging. Existing methods often cannot efficiently locate forged regions in such cases.
Shwetha Basavarajappa , Sathyanarayana Sarapady Venkatramanayya   +1 more
doaj   +1 more source

CMFDFormer: Transformer-based Copy-Move Forgery Detection with Continual Learning [PDF]

Copy-move forgery detection aims at detecting duplicated regions in a suspected forged image, and deep learning based copy-move forgery detection methods are in the ascendant. These deep learning based methods heavily rely on synthetic training data, and
Xia, Chao, Guan, Qingxiao, Dong, Wenqian, Zhang, Yifan, Yu, Nenghai, Liu, Yaqi, Xiao, Song   +6 more
core   +1 more source

Copy-Move Forgery Detection Technique Using Graph Convolutional Networks Feature Extraction

IEEE Access
In the development of image forensics, detection of Copy-Move Forgery (CMF) has become a major challenge due to the proliferation of image forgery techniques.
Varun Shinde, Vineet Dhanawat, Ahmad Almogren, Anjanava Biswas, Muhammad Bilal, Rizwan Ali Naqvi, Ateeq Ur Rehman   +6 more
doaj   +1 more source

Detecting copy-move forgery regions through multi-block features

, 2017
碩士本論文提出一個以多重區塊特徵提取的方式來偵測影像是否遭到複製移動竄改的攻擊，首先將影像分割出來的區塊進行不變動量值的特徵處理，再對不變動量值進行兩種不同特徵的提取，接著以這兩種特徵值對區塊進行分類，並且將每個類別集合成大類以增加區塊相似度的範圍，擷取在兩種特徵值分類中皆為同類別的區塊進行比對，如此降低區塊間的比對次數；另外，本方法利用不變動量值進行區塊比對，除能提升本方法對不同角度的偵測外，亦降低區塊的資料量，使得比對效率大幅提升，且能同時過濾極度不相似的區塊。在匹配階段 ...
王瀚;Wang, Han
core  

The Optimal Model for Copy-Move Forgery Detection in Medical Images. [PDF]

J Med Signals Sens
Amiri E, Mosallanejad A, Sheikhahmadi A.
europepmc   +1 more source

CFDMI-SEC: An optimal model for copy-move forgery detection of medical image using SIFT, EOM and CHM. [PDF]

PLoS One
Amiri E, Mosallanejad A, Sheikhahmadi A.
europepmc   +1 more source

Retracted: Design of Automated Deep Learning-Based Fusion Model for Copy-Move Image Forgery Detection. [PDF]

Comput Intell Neurosci, 2023
Intelligence And Neuroscience C.
europepmc   +1 more source

A comprehensive taxonomy on multimedia video forgery detection techniques: challenges and novel trends. [PDF]

Multimed Tools Appl, 2023
El-Shafai W, Fouda MA, El-Rabaie EM, El-Salam NA.   +3 more
europepmc   +1 more source