Effective and efficient pixel-level detection for diverse video copy-move forgery types
作者：
Highlights：
• An innovatively improved SIFT structure that addresses the thorough feature extraction in all forgery cases.
• A fast keypoint-label matching (FKLM) that creates groups of keypoint-label so that every high-dimensional feature is assigned into one of these groups.
• A coarse-to-fine filtering relying on intrinsic attributes of exact keypoint-matches is designed to reduce false keypoint-matches effectively.
• The adaptive block filling relying on true keypoint-matches contributes to the accurate and efficient suspicious region filling.
摘要
•An innovatively improved SIFT structure that addresses the thorough feature extraction in all forgery cases.•A fast keypoint-label matching (FKLM) that creates groups of keypoint-label so that every high-dimensional feature is assigned into one of these groups.•A coarse-to-fine filtering relying on intrinsic attributes of exact keypoint-matches is designed to reduce false keypoint-matches effectively.•The adaptive block filling relying on true keypoint-matches contributes to the accurate and efficient suspicious region filling.
论文关键词：Video copy-move forgery detection,Thorough feature extraction,Fast keypoint-label matching,Coarse-to-fine filtering,Adaptive block filling
论文评审过程：Received 20 February 2021, Revised 10 August 2021, Accepted 28 August 2021, Available online 30 August 2021, Version of Record 7 September 2021.
论文官网地址：https://doi.org/10.1016/j.patcog.2021.108286
