Object-Based Image Steganography Using Affine Transformation

The typical model of steganography has led the prisoners’ problem, in which two persons attempt to communicate covertly without alerting the warden. The general way to achieve this task is to embed the message in an innocuous-looking medium. In this paper, an object-based geometric embedding technique is proposed for solving the prisoners’ problem. The main idea is to embed secret data through distorting a given object and the distorted object still looks natural. In the embedding process, the secret message is first converted into coefficients of an affine transformation. Then, the coordinates of each pixel of a selected object in the cover-image are recomputed by this affine transformation. Since these coefficients are restricted in a specific range, the transformed object looks natural. In the extracting process, a coarse-to-fine iterative search is proposed to accelerate the object location and the message extraction. Experimental results show that all transformed objects can be located precisely and the whole hidden message can be extracted correctly even if the stego-image is stored in various compression formats and rates. Furthermore, the embedded message is robust enough when the stego-image format is converted from GIF to JPEG, and vice versa.