Digital Image Forensics using Deep Learning
원문 초록
During the investigation of criminal activity when evidence is available, the issue at hand is determining the credibility of the video and ascertaining that the video is real. Today, one way to authenticate the footage is to identify the camera that was used to capture the image or video in question. While a very common way to do this is by using image meta-data, this data can easily be falsified by changing the video content or even splicing together content from two different cameras. Given the multitude of solutions proposed to this problem, it is yet to be sufficiently solved. The aim of our project is to build an algorithm that identifies which camera was used to capture an image using traces of information left intrinsically in the image, using filters, followed by a deep neural network on these filters. Solving this problem would have a big impact on the verification of evidence used in criminal and civil trials and even news reporting.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Can ChatGPT Perform Image Splicing Detection? A Preliminary Study
FIRE: Robust Detection of Diffusion-Generated Images via Frequency-Guided Reconstruction Error
Is JPEG AI going to change image forensics?
Deep Image Restoration For Image Anti-Forensics
Fusion Transformer with Object Mask Guidance for Image Forgery Analysis
An Effective Image Copy-Move Forgery Detection Using Entropy Information
토론
이 논문과 연결된 포럼 글이 아직 없습니다.