Image forgery detection for high resolution images using SIFT and RANSAC algorithm
원문 초록
Cloning (copy-move forgery) is a malicious tampering attack with digital images where a part of image is copied and pasted within the image to conceal the important details of image without any obvious traces of manipulation. This type of tampering attacks leaves a big question of authenticity of images to the forensics. Many techniques are proposed in the past few years after powerful software’s are developed to manipulate the image. The proposed scheme is involved with both the block based and feature point extraction based techniques to extract the forged regions more accurately. The proposed algorithm mainly involves in matching the tentacles of same features extracted from each block by computing the dot product between the unit vectors. Random Sample Consensus (RANSAC) algorithm is used to extract the matched regions. The experimental result of the algorithm which is proposed indicates that, it can extract more accurate results compared with existing forgery detection methods.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
SFNet: Fusion of Spatial and Frequency-Domain Features for Remote Sensing Image Forgery Detection
Learning Universal Features for Generalizable Image Forgery Localization
FakeShield: Explainable Image Forgery Detection and Localization via Multi-modal Large Language Models
Deep Image Restoration For Image Anti-Forensics
Deep Image Composition Meets Image Forgery
Fusion Transformer with Object Mask Guidance for Image Forgery Analysis
토론
이 논문과 연결된 포럼 글이 아직 없습니다.