Name
Abstract | ||
|---|---|---|
In this paper, we propose a novel data hiding method based on histogram framework which is essentially different from the conventional histogram-based data hiding methods. The conventional methods always use the peak point to embed the secret data and before the embedding all pixels between peak point and zero point must be shifted to zero point to provide an extra space for embedding. The distortion is mainly caused by this shifting operation. We propose using the border point of the histogram instead of peak point to embed the secret data so that the shifting can be completely avoided. Because there are no pixels between border point and extremum point (i.e. 0 or 255), there is no shifting before embedding. Then, to increase the embedding capacity, more border points are needed for embedding. Therefore, the localization is exploited to divide the cover image into non-overlapping blocks to generate more border points. Compared with other histogram-based data hiding methods, our proposed method provides higher image quality because the shifting is avoided, and the embedding capacity is also high due to the localization. Experimental results show that the PSNR of our proposed method is at least 5–10 dB higher than the related histogram-based data hiding methods under the same embedding capacity. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/s11042-014-2368-5 | Multimedia Tools and Applications |
Keywords | Field | DocType |
Data hiding, Histogram shifting, Peak point, Border point, Localization | Histogram,Computer vision,Embedding,Pattern recognition,Computer science,Information hiding,Image quality,Histogram matching,Artificial intelligence,Pixel,Distortion | Journal |
Volume | Issue | ISSN |
75 | 2 | 1573-7721 |
Citations | PageRank | References |
0 | 0.34 | 18 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhibin Pan | 1 | 276 | 37.59 |
| Sen Hu | 2 | 211 | 9.99 |
| Xiaoxiao Ma | 3 | 202 | 14.68 |
| Lingfei Wang | 4 | 24 | 1.40 |