On Establishing Edge Adaptive Grid for Bi-Level Image Data Hiding
Cao, H and Kot, A.C
Information Forensics and Security, IEEE Transactions on
Published, 2013
Abstract:
we propose in this paper a novel edge-adaptive data hiding method for authenticating binary host images. Through establishing dense edge-adaptive grid (EAG) along the object contours, we use a simple binary image to show that EAG more efficiently selects good data carrying pixel locations (DCPL) associated with “L-shape” patterns than block-based methods. Our method employs a dynamic system structure with the re-designed fundamental content adaptive processes (CAP) switch to iteratively trace new contour segments and to search for new DCPLs. By maintaining and updating a location status map, a protective mechanism is proposed to preserve the context of each CAP and their corresponding outcomes. We prove that our method is robust against the interferences caused by close-by contours, image noises, and invariantly selects a same sequence of DCPLs for an arbitrary binary host image and its various marked versions. Comparison shows that our method achieves a good trade-off between large hiding payload and minimal visual distortion as compared with several classic prior arts for diverse types of binary host images. Moreover, our method well supports state-of-the-art hybrid authentication that integrates data hiding and modern cryptographic techniques.
-----------------------
Download:
Full Paper in PDF
An embedding example is downloadable here.
Data Hiding Demo Software for download: Installation Package, Readme
Binary Image Dataset for experiment is downloadable here.
Please cite the following papers:
[1] H. Cao and A.C. Kot, “On Establishing Edge Adaptive Grid for Bi-Level Image Data Hiding,” IEEE Trans. on Information Forensics and Security (TIFS), vol. 8(9), pp. 1508-1518, 2013
[2] H. Cao and A.C. Kot, “EAG: Edge Adaptive Grid Data Hiding for Binary Image Authentication,” in Proc. APSIPA ASC, pp. 1-6, 2012