Recently Zhang et al described an algorithm for the detection of ±1 LSB steganography based on the statistics of the amplitudes of local extrema in the greylevel histogram. Experimental results demonstrated performance comparable or superior to other state-of-the-art algorithms. In this paper, we describe improvements to this algorithm to (i) reduce the noise associated with border effects in the histogram, and (ii) extend the analysis to amplitudes of local extrema in the 2D adjacency

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... . Experimental results on a composite database of 7125 images, averaged over a 20-fold cross validation, with classification based on Fisher linear discriminant analysis, demonstrate that the improved algorithm exhibits significantly better performance. The experimental results are reported in the form of receiver operating characteristic (ROC) curves and summarized by computing the area under the ROC curve (AUC). The new algorithm, using 10 features derived from the 1D and 2D histograms, has an AUC value of 0.77 compared to 0.57 for the original algorithm. It also significantly outperforms other state-of-the-art steganalysers.