  Image splicing detection is of fundamental importance in digital forensics
and therefore has attracted increasing attention recently. In this paper, a
color image splicing detection approach is proposed based on Markov transition
probability of quaternion component separation in quaternion discrete cosine
transform (QDCT) domain and quaternion wavelet transform (QWT) domain. Firstly,
Markov features of the intra-block and inter-block between block QDCT
coefficients are obtained from the real part and three imaginary parts of QDCT
coefficients respectively. Then, additional Markov features are extracted from
luminance (Y) channel in quaternion wavelet transform domain to characterize
the dependency of position among quaternion wavelet subband coefficients.
Finally, ensemble classifier (EC) is exploited to classify the spliced and
authentic color images. The experiment results demonstrate that the proposed
approach can outperforms some state-of-the-art methods.
