Geometrically Invariant Object-Based Watermarking using SIFT Feature

Pham, Viet Quoc; Miyaki, Takashi; Yamasaki, Toshihiko; Aizawa, Kiyoharu

doi:10.1109/icip.2007.4379868

Cited by 29 publications

(21 citation statements)

References 7 publications

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“…And in this paper, we only focus on the robustness to non-linear geometrical attacks. For the performance to conventional attacks such as affine transform, JPEG compression, filtering, rotation, resizing, noise, and so on, please refer to [16].…”

Section: Methodsmentioning

confidence: 99%

“…In our method [16], [18], a single bit is embedded to each block by modifying two arbitrary DCT coefficients f (x i , y i ), f (y i , x i ) (i = 0, 1) as in the following;…”

Section: Embeddingmentioning

confidence: 99%

“…In [14], a SIFT-based watermarking scheme with polar mapping was developed. Our previous work can also handle affine transform [16]. For further discussion of linear geometric distortion attacks, please refer to [12].…”

Section: Introductionmentioning

confidence: 99%

“…The linearly distorted content was restored to its original size and shape by a combination of the SIFT and random sample consensus (RANSAC) algorithms [20]. The robustness to conventional attacks, such as lossy compression, image filtering, affine transform, and replacement has already been presented in [16]. However, as shown in Sect.…”

Section: Introductionmentioning

confidence: 99%

“…[18] was based on the geometrically invariant object-based watermarking [16]. In [16], the protected content within the attacked content was automatically detected using the SIFT algorithm [19].…”

Section: Introductionmentioning

confidence: 99%

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SIFT-Based Non-blind Watermarking Robust to Non-linear Geometrical Distortions

Yamasaki

Aizawa

2013

IEICE Trans. Inf. & Syst.

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SUMMARYThis paper presents a non-blind watermarking technique that is robust to non-linear geometric distortion attacks. This is one of the most challenging problems for copyright protection of digital content because it is difficult to estimate the distortion parameters for the embedded blocks. In our proposed scheme, the location of the blocks are recorded by the translation parameters from multiple Scale Invariant Feature Transform (SIFT) feature points. This method is based on two assumptions: SIFT features are robust to non-linear geometric distortion and even such nonlinear distortion can be regarded as "linear" distortion in local regions. We conducted experiments using 149,800 images (7 standard images and 100 images downloaded from Flickr, 10 different messages, 10 different embedding block patterns, and 14 attacks). The results show that the watermark detection performance is drastically improved, while the baseline method can achieve only chance level accuracy. key words: watermarking, scale invariant feature transform (SIFT), nonlinear geometric distortion attacks

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Section: Methodsmentioning

confidence: 99%

“…In our method [16], [18], a single bit is embedded to each block by modifying two arbitrary DCT coefficients f (x i , y i ), f (y i , x i ) (i = 0, 1) as in the following;…”

Section: Embeddingmentioning

confidence: 99%