Yu-Feng Hsu, Shih-Fu Chang. Image Splicing Detection Using Camera Response Function Consistency and Automatic Segmentation. In International Conference on Multimedia and Expo (ICME), Beijing, China, July 2007.
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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 locally 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 further 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.
@InProceedings{hsu:icme07,
Author = {Hsu, Yu-Feng and Chang, Shih-Fu},
Title = {Image Splicing Detection Using Camera Response Function Consistency and Automatic Segmentation},
BookTitle = {International Conference on Multimedia and Expo (ICME)},
Address = {Beijing, China},
Month = {July},
Year = {2007}
}
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