Name
Abstract | ||
|---|---|---|
A non-saliency guided watermarking approach is introduced where the watermark is embedded in natural images based on three measures, namely, non-saliency, heterogeneity and brightness. The three measures aim to exploit the main characteristics of the human visual system (HVS) for the purpose of embedding watermarks in images. The proposed method has the following advantages: (1) increasing the imperceptibility of the watermark through modeling HVS, (2) robustness to different attacks through embedding the data into non-salient areas with strong features and (3) increasing the watermarking capacity of labeling image pixels as appropriate or inappropriate candidates by using the continuous non-saliency heterogeneity-brightness spectrum as opposed to binary labeling schemes as suggested by other methods. A variety of experiments demonstrate the superiority of the proposed method over existing state-of-the-art methods in terms of robustness and imperceptibility. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/CRV.2016.12 | 2016 13th Conference on Computer and Robot Vision (CRV) |
Keywords | Field | DocType |
Watermarking,human visual system,nonsaliency | Computer vision,Digital watermarking,Embedding,Pattern recognition,Human visual system model,Computer science,Salience (neuroscience),Robustness (computer science),Watermark,Pixel,Artificial intelligence,Binary number | Conference |
ISBN | Citations | PageRank |
978-1-5090-2492-6 | 1 | 0.35 |
References | Authors | |
17 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ahmed Gawish | 1 | 1 | 1.02 |
| Christian Scharfenberger | 2 | 138 | 10.61 |
| Hongbo Bi | 3 | 1 | 0.35 |
| Alexander Wong | 4 | 351 | 69.61 |
| Paul W. Fieguth | 5 | 612 | 54.17 |
| David A. Clausi | 6 | 1082 | 89.57 |