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Record W2161475444 · doi:10.1109/mwscas.2009.5236026

A computation structure for 2-D DCT watermarking

2009· article· en· W2161475444 on OpenAlexaff
Shaofeng An, Chunyan Wang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Steganography and Watermarking Techniques
Canadian institutionsConcordia University
Fundersnot available
KeywordsDiscrete cosine transformDigital watermarkingWatermarkComputationTrellis quantizationReduction (mathematics)Block (permutation group theory)Computer scienceAlgorithmImage (mathematics)MathematicsArtificial intelligenceComputer visionImage processingImage compression

Abstract

fetched live from OpenAlex

In this paper, a new computation structure of image watermarking in DCT domain is presented. This structure employs a single DCT block, instead of two in many existing DCT watermarking systems, for the DCT computation of the image signal and that of the watermark. Using the single DCT block does not double the time required for the two 2-D DCT computations, as the amount of the calculations in this structure is effectively reduced compared to those with two DCT blocks. By using a special condensed 2-D DCT algorithm, the DCT computation of the watermark is divided into two parts and only the part necessary and sufficient for the watermarking is performed to achieve a significant reduction of the overall computation. This structure can be easily implemented into a circuit. Using the single DCT block, the hardware reduction in the 2-D DCT part of the watermarking circuit can reach 50% with the time delay increase of only 34%. It has been confirmed by the preliminary results of the FPGA implementation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.729
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.270
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2009
Admission routes1
Has abstractyes

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