Digital Media Forensic Detection
Digital Media Forensic Detection is a research topic within Computer Vision and Pattern Recognition. Science Explorer counts 21k research works in it since 1954. 9.8% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on the detection and identification of digital image forgeries, including techniques such as copy-move forgery detection, sensor pattern noise analysis, JPEG compression history estimation, camera model identification, splicing detection, and tampering localization. The papers also explore the application of deep learning methods for image forensics and the detection of inconsistencies in image manipulation.
- Image Forgery Detection
- Digital Forensics
- Copy-Move Forgery
- Sensor Pattern Noise
- JPEG Compression
- Camera Model Identification
- Deep Learning
- Splicing Detection
- Tampering Localization
- Resampling Detection
- Research works
- 21k fractional, since 1954
- In the world top 10%
- 2.1k per year above
- Top-10% rate
- 9.8% share of its works in the world top 10%
- Growth, 2018-21 → 2022-25
- +57% the tick is no change
- Largest producer
China
43% of the 10 largest, 2022-now
Drawing this view