An Image Splicing Detection Method Based on PCA Minimum Eigenvalues
This paper presents a novel and effective image splicing forgery detection method based on the inconsistency of irrelevant components between the original and the tampered regions. The specific irrelevant components can be described by the minimum eigenvalues obtained by the principal component analysis (PCA) without knowing any prior information. To avoid the impact of local structures, a pixel and its nearest neighbors are taken as a block and the input matrix of PCA are gotten through self similarity pixel strategy (SSS) from the block, which extracts a local minimum eigenvalue for every pixel. The experimental results on several forged image datasets demonstrate that our method achieves competitive detection accuracy compared with two other region based methods.
J. Inf. Hiding Multim. Signal Process.