Digital Watermarking Scheme Based on Machine Learning for the IHC Evaluation Criteria

Sakuma, Ryo; Kang, Hyunho; Iwamura, Keiichi; Echizen, Isao

doi:10.1007/978-3-319-63856-0_45

Cited by 1 publication

(1 citation statement)

References 7 publications

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“…Specifically, its objective is to develop standard evaluation criteria and sponsor watermark competitions based on these criteria. As a part of this objective, a benchmarking study was conducted on various types of image, video, and audio watermarking, based on standardized criteria [8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

MPEG and DA-AD Resilient DCT-Based Video Watermarking Using Adaptive Frame Selection

Hou

2021

Electronics

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We present a robust video watermarking scheme and report the detailed robustness of the video watermarking assessed based on standard criteria obtained from Information Hiding and its Criteria (IHC) Committee. Using discrete cosine transform domain spread-spectrum watermarking, our system achieves robustness under various non-hostile video processing techniques, including MPEG compression and digital/analog–analog/digital (DA-AD) conversion. The proposed system ensures that a 16-bit embedded sequence can be extracted through adaptive frame selection in any 15-s interval, even with a long video clip. To evaluate the performance of the proposed watermarking scheme, we conducted robustness tests under a DA-AD conversion environment, based on the MPEG-4 part 10 (H.264) codec. The experiment results obtained indicate that, in addition to being robust against non-hostile video processes, the proposed method achieves invisibility. The assessment of the developed watermarking scheme also satisfies the third edition of the IHC video watermarking evaluation criteria.

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Section: Introductionmentioning

confidence: 99%

MPEG and DA-AD Resilient DCT-Based Video Watermarking Using Adaptive Frame Selection

Hou

2021

Electronics

View full text Add to dashboard Cite

show abstract

Digital Watermarking Scheme Based on Machine Learning for the IHC Evaluation Criteria

Cited by 1 publication

References 7 publications

MPEG and DA-AD Resilient DCT-Based Video Watermarking Using Adaptive Frame Selection

MPEG and DA-AD Resilient DCT-Based Video Watermarking Using Adaptive Frame Selection

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