Secure halftone image steganography based on density preserving and distortion fusion

Abstract

Most state-of-the-art halftone image steganographic methods measure the flipping distortion according to the statistics of the image database but neglect the characteristic of a single image. In this paper, a halftone image steganography based on density preserving and distortion fusion is proposed for minimizing the flipping distortion. Different from ordinary binary images, halftone images express the texture information by the intensity of local regions that are represented by the pixel density. Based on the density distribution of a halftone image, the embedding costs defined by a single existing distortion function are modified adaptively to maintain the original texture structure as much as possible. Furthermore, to select more appropriate flipped pixels, a distortion fusion strategy is developed from the perspective of anti-steganographic analysis, which can be applied to a batch of distortion functions. Finally, the syndrome-trellis code (STC) is applied to minimize the embedding distortion for playing the advantage of the distortion measurement. Experimental results show that the proposed steganographic scheme achieves great visual quality and strong statistical security without degrading the embedding capacity.