A vision-based masking model for spread-spectrum image watermarking

Kutter, Martin; Winkler, Stefan

doi:10.1109/83.977879

Cited by 161 publications

(78 citation statements)

References 19 publications

(23 reference statements)

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“…For instance, Ferwerda et al proposed a visual masking model allowing one to predict the influence of one visual pattern on another [FSPG97]. In a different field, Kutter et al designed a vision-based masking model for spread-spectrum image watermarking [KW02]. Finally, Daly exploited both luminance and contrast masking for the definition of VDP [Dal93].…”

Section: Human Perceptionmentioning

confidence: 99%

Perceptual Metrics for Static and Dynamic Triangle Meshes

Corsini

Larabi

Lavoué

et al. 2013

Computer Graphics Forum

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Almost all mesh processing procedures cause some more or less visible changes in the appearance of objects represented by polygonal meshes. In many cases, such as mesh watermarking, simplification or lossy compression, the objective is to make the change in appearance negligible, or as small as possible, given some other constraints. Measuring the amount of distortion requires taking into account the final purpose of the data. In many applications, the final consumer of the data is a human observer, and therefore the perceptibility of the introduced appearance change by a human observer should be the criterion that is taken into account when designing and configuring the processing algorithms. In this review, we discuss the existing comparison metrics for static and dynamic (animated) triangle meshes. We describe the concepts used in perception-oriented metrics used for 2D image comparison, and we show how these concepts are employed in existing 3D mesh metrics. We describe the character of subjective data used for evaluation of mesh metrics and provide comparison results identifying the advantages and drawbacks of each method. Finally, we also discuss employing the perception-correlated metrics in perception-oriented mesh processing algorithms.

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Section: Human Perceptionmentioning

confidence: 99%

Perceptual Metrics for Static and Dynamic Triangle Meshes

Corsini

Larabi

Lavoué

et al. 2013

Computer Graphics Forum

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“…19,20 It uses spread-spectrum modulation to insert a watermark with variable amplitude and density in the spatial domain. In contrast to the other four algorithms, it considers the temporal content changes in the video.…”

Section: The Video Watermarking Scheme Developed By Alpvisionmentioning

confidence: 99%

Toward perceptual metrics for video watermark evaluation

Gelasca

Ebrahimi

2003

Applications of Digital Image Processing XXVI

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Assessing and comparing the performance of watermarking algorithms is difficult. The visibility of the watermark is an important aspect in this process. In this paper, we propose two metrics for evaluating the visual impact of video watermarks. Based on several different watermarking algorithms and video sequences, we identify the most prominent impairments as spatial noise and temporal flicker. We design the corresponding measurement algorithms and corroborate their performance through subjective experiments.

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“…Kutter at al. [8] investigated watermarking of luminance and blue-channels using a perceptual model, which takes into account the sensitivity and the masking behaviour of the HVS. Nasir et al [9] suggested embedding the watermark into luminance component of the color image and use image normalization technique to reduce the effect of synchronization errors.…”

Section: Introductionmentioning

confidence: 99%

Robust Colour Image Watermarking Scheme Based on Feature Points and Image Normalization in DCT Domain

Nasir¹

2014

Computer Science &Amp; Information Technology ( CS &Amp; IT )

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Geometric attacks can desynchronize the location of the watermark and hence cause incorrect watermark detection. This paper presents a robust colour image watermarking scheme based on visually significant feature points and image normalization technique. The feature points are used as synchronization marks between watermark embedding and detection. The watermark is embedded into the non overlapped normalized circular regions in the luminance component or the blue component of a color image. The embedding of the watermark is carried out by modifying the DCT coefficients values in selected blocks. The original unmarked image is not required for watermark extraction Experimental resultsshow that the proposed scheme successfully makes the watermark perceptually invisible as well as robust to common signal processing and geometric attacks.

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A vision-based masking model for spread-spectrum image watermarking

Cited by 161 publications

References 19 publications

Perceptual Metrics for Static and Dynamic Triangle Meshes

Perceptual Metrics for Static and Dynamic Triangle Meshes

Toward perceptual metrics for video watermark evaluation

Robust Colour Image Watermarking Scheme Based on Feature Points and Image Normalization in DCT Domain

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