Detecting digital image splicing in chroma spaces

Abstract

Detecting splicing traces in the tampering color space is usually a tough work. However, it is found that image splicing which is difficult to be detected in one color space is probably much easier to be detected in another one. In this paper, an efficient approach for passive color image splicing detection is proposed. Chroma spaces are introduced in our work compared with commonly used RGB and luminance spaces. Four gray level run-length run-number (RLRN) vectors with different directions extracted from de-correlated chroma channels are employed as distinguishing features for image splicing detection. Support vector machine (SVM) is used as a classifier to demonstrate the performance of the proposed feature extraction method. Experimental results have shown that that RLRN features extracted from chroma channels provide much better performance than that extracted from R, G, B and luminance channels. © 2011 Springer-Verlag.