Distortion Function for Emoji Image Steganography

Nowadays, emoji image is widely used in social networks. To achieve covert communication in emoji images, this paper proposes a distortion function for emoji images steganography. The profile of image content, the intra- and inter-frame correlation are taken into account in the proposed distortion function to fit the unique properties of emoji image. The three parts are combined together to measure the risks of detection due to the modification on the cover data. With the popular syndrome trellis coding (STC), the distortion of stego emoji image is minimized using the proposed distortion function. As a result, less detectable artifacts could be found in the stego images. Experimental results show that the proposed distortion function performs much higher undetectability than current state-of-the-art distortion function HILL which is designed for natural image.