title: LDFT-based watermarking resilient to local desynchronization attacks.
abstract: Up to now, a watermarking scheme that is robust against desynchronization attacks (DAs) is still a grand challenge. Most image watermarking resynchronization schemes in literature can survive individual global DAs (e.g., rotation, scaling, translation, and other affine transforms), but few are resilient to challenging cropping and local DAs. The main reason is that robust features for watermark synchronization are only globally invariable rather than locally invariable. In this paper, we present a blind image watermarking resynchronization scheme against local transform attacks. First, we propose a new feature transform named local daisy feature transform (LDFT), which is not only globally but also locally invariable. Then, the binary space partitioning (BSP) tree is used to partition the geometrically invariant LDFT space. In the BSP tree, the location of each pixel is fixed under global transform, local transform, and cropping. Lastly, the watermarking sequence is embedded bit by bit into each leaf node of the BSP tree by using the logarithmic quantization index modulation watermarking embedding method. Simulation results show that the proposed watermarking scheme can survive numerous kinds of distortions, including common image-processing attacks, local and global DAs, and noninvertible cropping.
authors.forename: Huawei
authors.initials: H
authors.lastname: Tian
authors.forename: Yao
authors.initials: Y
authors.lastname: Zhao
authors.forename: Rongrong
authors.initials: R
authors.lastname: Ni
authors.forename: Lunming
authors.initials: L
authors.lastname: Qin
authors.forename: Xuelong
authors.initials: X
authors.lastname: Li
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003196:Computer Graphics; D016494:Computer Security; D044962:Data Compression / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated / Q000379:methods*; D011356:Product Labeling / Q000379:methods*