Steganalysis of Binary Cartoon Image using Distortion Measure

We present a steganalysis technique for data hiding in binary cartoon images. Due to the perturbation from the embedding, the contours of a stego binary cartoon image are distorted. When calculating the distortion of the image based on a distortion measure, the distortion score between a stego image and its de-noised version should be different from that between an original image and its de-noised version. Different binary image distortion measures are used to calculate the distortion scores, which are used as the features for classification. The sequential floating forward search (SFFS) method is used to search for the combination of the features that yields the best classification results.