Results 51 to 60 of about 13,849 (178)
Multibranch Collaboration and Segmented Training Network for Image Forgery Comprehensive Detection
IET BiometricsWith the rise of sophisticated image manipulation techniques, image detection forgeries have become increasingly challenging. This paper presents a novel deep learning framework, the multibranch collaboration and segmented training network (MBC-STN), for
Jing Chang +3 more
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False Matches Removing in Copy-Move Forgery Detection Algorithms
Al-Mustansiriyah Journal of Science, 2020 Today the technology age is characterized by spreading of digital images. The most common form of transfer the information in magazines, newspapers, scientific journals and all types of social media.
muthana salih mahdi, Saad N. Alsaad
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Refining PRNU-based detection of image forgeries [PDF]
2016 Digital Media Industry & Academic Forum (DMIAF), 2016 Photo Response Non-Uniformity (PRNU) noise can be considered as a spread-spectrum watermark embedded in every image taken by the source imaging device. It has been effectively used for localizing the forgeries in digital images. The noise residual extracted from the image in question is compared with the reference PRNU in a sliding-window based manner.
Xufeng Lin, Chang-Tsun Li
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Camera-based Image Forgery Localization using Convolutional Neural Networks
, 2018 Camera fingerprints are precious tools for a number of image forensics tasks. A well-known example is the photo response non-uniformity (PRNU) noise pattern, a powerful device fingerprint.
Cozzolino, Davide, Verdoliva, Luisa
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Investigating Human Factors in Image Forgery Detection [PDF]
Proceedings of the 1st ACM International Workshop on Human Centered Event Understanding from Multimedia, 2014 In today's age of internet and social media, one can find an enormous volume of forged images on-line. These images have been used in the past to convey falsified information and achieve harmful intentions. The spread and the effect of the social media only makes this problem more severe.
Parag S. Chandakkar, Baoxin Li
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Face Forgery Detection and Attribution via Prototype Disentanglement [PDF]
Jisuanji kexue yu tansuoThe detection and attribution of face forgery aims to determine whether a face in an image or video has been manipulated or synthesized using Deepfake techniques, as well as to further analyze the Deepfake method behind it.
QIAN Fei, LI Wei, CHEN Peng, CHEN Haoran, XIE Lipeng, LIU Liyuan
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, 2018 In this paper, we consider the problem of detecting counterfeit identity documents in images captured with smartphones. As the number of documents contain special fonts, we study the applicability of convolutional neural networks (CNNs) for detection of ...
Berenguel +4 more
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Iranian Journal of Electrical and Electronic Engineering, 2020 Increased popularity of digital media and image editing software has led to the spread of multimedia content forgery for various purposes. Undoubtedly, law and forensic medicine experts require trustworthy and non-forged images to enforce rights.
A. Fattahi, S. Emadi
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Image Splicing Localization Using A Multi-Task Fully Convolutional Network (MFCN)
, 2017 In this work, we propose a technique that utilizes a fully convolutional network (FCN) to localize image splicing attacks. We first evaluated a single-task FCN (SFCN) trained only on the surface label.
Kuo, C. -C. Jay +2 more
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AISMSNet: Advanced Image Splicing Manipulation Identification Based on Siamese Networks
Applied SciencesThe exponential surge in specialized image editing software has intensified visual forgery, with splicing attacks emerging as a popular forgery technique.
Ana Elena Ramirez-Rodriguez +4 more
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