Content-Based Watermarking by Geometric Warping and Feature-Based Image Segmentation

Pröfrock, Dima; Schlauweg, Mathias; Müller, Erika

doi:10.1007/978-0-387-72500-0_22

Cited by 5 publications

(7 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Image Attribution methods bind an image to data on its provenance, via embedded metadata [3,11], watermarking [21,9,30,1], or perceptual hashing [29,27,4,22]. Emerging standards securely transport a cryptographically signed edit history within image metadata [3,11].…”

Section: Related Workmentioning

confidence: 99%

Deep Image Comparator: Learning to Visualize Editorial Change

Black

Bui

Jin

et al. 2021

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

View full text Add to dashboard Cite

We present a novel architecture for comparing a pair of images to identify image regions that have been subjected to editorial manipulation. We first describe a robust near-duplicate search, for matching a potentially manipulated image circulating online to an image within a trusted database of originals. We then describe a novel architecture for comparing that image pair, to localize regions that have been manipulated to differ from the retrieved original. The localization ignores discrepancies due to benign image transformations that commonly occur during online redistribution. These include artifacts due to noise and recompression degradation, as well as out-of-place transformations due to image padding, warping, and changes in size and shape. Robustness towards out-of-place transformations is achieved via the end-to-end training of a differentiable warping module within the comparator architecture. We demonstrate effective retrieval and comparison of benign transformed and manipulated images, over a dataset of millions of photographs.

show abstract

Section: Related Workmentioning

confidence: 99%

Deep Image Comparator: Learning to Visualize Editorial Change

Black

Bui

Jin

et al. 2021

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

View full text Add to dashboard Cite

show abstract

“…It is used for application such as watermarking and data hiding. In [3], [4], [5] methods are presented, which embed additionally information (watermarks) into images or videos by warping. The watermark information is coded e.g.…”

Section: Introductionmentioning

confidence: 99%

A study of video-quality relevant warping parameters

Pröfrock

Schlauweg

Müller

2008

2008 IEEE 10th Workshop on Multimedia Signal Processing

Self Cite

View full text Add to dashboard Cite

In this paper, we present a study of video-quality relevant warping parameters. Motivation of our work is to estimate the influence of warping on the quality of videos. This is required for watermarking embedding and attacking approaches that base on warping of images or videos. Therefore, we propose a universal set of parameters, which can be used to describe any warping field. Aim is to estimate out of these parameters the video quality after warping. To show the correlation between parameters and video quality, we performed a study and present the results in this paper.

show abstract

“…Bergman and Davidson (2005) used SVD as a medium to embed information and give steganography scheme. Also Pröfrock et al (2008) proposed a SVD based watermarking and steganography schemes where watermarking scheme was designed by slightly modifying the most significant singular values for encoding vital data in the media. Lai (2011) presented a SVD-based watermarking technique considering human visual characteristics through block selection with Discrete Cosine Transformation (DCT) followed by SVD.…”

Section: Introductionmentioning

confidence: 99%

Reliable SVD based Semi-blind and Invisible Watermarking Schemes

Moulick¹,

Arora²,

Jain³

et al. 2015

Preprint

View full text Add to dashboard Cite

A semi-blind watermarking scheme is presented based on Singular Value Decomposition (SVD), which makes essential use of the fact that, the SVD subspace preserves significant amount of information of an image and is a one way decomposition. The principal components are used, along with the corresponding singular vectors of the watermark image to watermark the target image. For further security, the semi-blind scheme is extended to an invisible hash based watermarking scheme. The hash based scheme commits a watermark with a key such that, it is incoherent with the actual watermark, and can only be extracted using the key. Its security is analyzed in the random oracle model and shown to be unforgeable, invisible and satisfying the property of non-repudiation.

show abstract

Content-Based Watermarking by Geometric Warping and Feature-Based Image Segmentation

Cited by 5 publications

References 3 publications

Deep Image Comparator: Learning to Visualize Editorial Change

Deep Image Comparator: Learning to Visualize Editorial Change

A study of video-quality relevant warping parameters

Reliable SVD based Semi-blind and Invisible Watermarking Schemes

Contact Info

Product

Resources

About