A Preliminary Study of Steganalysis on Half-tone Image

Abstract

In this work, a steganalysis method is proposed to identify half-tone stego images. The proposed steganalysis eliminates the need to perform inverse half-toning as in the conventional methods, and it detects the stegos generated by DHST and DHED. A suspicious half-tone image is first filtered to generate a pseudo-grayscale image and converted into a binary image. The dark regions in the output binary image are utilized as the mask to generate an intermediate image on which the proposed pattern localization analysis is carried out. 25 signal-to-noise ratios are collected to form the discriminating feature vector. This feature vector is then fed into the support vector machine for training and validation purposes. Results suggest that the proposed steganalysis technique can distinguish half-tone stegos from cover images with precision of 0.9603 and 0. 8407 for DHED and DHST, respectively, even when the secret message length is merely 10% of the maximum payload.