Image Splicing Detection Using Camera Response Function Consistency and Automatic Segmentation
| Type of publication: | Inproceedings |
| Citation: | hsu-chang-icme-07 |
| Booktitle: | IEEE International Conference on Multimedia and Expo |
| Year: | 2007 |
| Location: | Beijing, China |
| Abstract: | We propose a fully automatic spliced image detection method based on consistency checking of camera characteristics among different areas in an image. A test image is first segmented into distinct areas. One camera response function (CRF) is estimated from each area using geometric invariants from lo- cally planar irradiance points (LPIPs). To classify a boundary segment between two areas as authentic or spliced, CRF cross fitting scores and area intensity features are computed and fed to SVM-based classifiers. Such segment-level scores are fur- ther fused to form the image-level decision. Tests on both the benchmark data set and an unseen high-quality spliced data set reach promising performance levels with 70% precision and 70% recall. |
| Keywords: | |
| Authors | |
| Added by: | [ADM] |
| Total mark: | 0 |
|
Attachments
|
|
|
|
|
Code
|
|
|
|
|
|
Data
|
|
|
|
|
|
Notes
|
|
|
|
|
