A bibliography on blind methods for identifying image forgery
Image Communication
Detecting digital image splicing in chroma spaces
IWDW'10 Proceedings of the 9th international conference on Digital watermarking
Digital image splicing detection based on approximate run length
Pattern Recognition Letters
Markovian rake transform for digital image tampering detection
Transactions on data hiding and multimedia security VI
Digital image splicing detection based on Markov features in DCT and DWT domain
Pattern Recognition
Improved run length based detection of digital image splicing
IWDW'11 Proceedings of the 10th international conference on Digital-Forensics and Watermarking
An image splicing detection based on interpolation analysis
PCM'12 Proceedings of the 13th Pacific-Rim conference on Advances in Multimedia Information Processing
Image splicing verification based on pixel-based alignment method
IWDW'12 Proceedings of the 11th international conference on Digital Forensics and Watermaking
| Hi-index | 0.00 |
In this paper, a simple but efficient approach for blind image splicing detection is proposed. Image splicing is a common and fundamental operation used for image forgery. The detection of image splicing is a preliminary but desirable study for image forensics. Passive detection approaches of image splicing are usually regarded as pattern recognition problems based on features which are sensitive to splicing. In the proposed approach, we analyze the discontinuity of image pixel correlation and coherency caused by splicing in terms of image run-length representation and sharp image characteristics. The statistical features extracted from image run-length representation and image edge statistics are used for splicing detection. The support vector machine (SVM) is used as the classifier. Our experimental results demonstrate that the two proposed features outperform existing ones both in detection accuracy and computational complexity.