%0 Conference Proceedings
%F dvmmPub11
%A Ng, Tian-Tsong
%A Chang, Shih-Fu
%A Sun, Qibin
%T Blind Detection of Photomontage Using Higher Order Statistics
%B IEEE International Symposium on Circuits and Systems (ISCAS)
%C Vancouver, Canada
%X In this paper, we investigate the prospect of using bicoherence features for blind image splicing detection. Image splicing is an essential operation for digital photomontaging, which in turn is a technique for creating image forgery. We examine the properties of bicoherence features on a data set, which contains image blocks of diverse image properties. We then demonstrate the limitation of the baseline bicoherence features for image splicing detection. Our investigation has led to two suggestions for improving the performance of the bicoherence features, i.e., estimating the bicoherence features of the authentic counterpart and incorporating features that characterize the variance of the feature performance. The features derived from the suggestions are evaluated with Support Vector Machine (SVM) classification and shown to improve the image splicing detection accuracy from 62% to about 70%
%U http://www.ee.columbia.edu/dvmm/publications/04/ngISCAS04.pdf
%8 May
%D 2004